The AI effect occurs when onlookers discount the behavior of an artificial intelligence program as not "real" intelligence.
The author Pamela McCorduck
writes: "It's part of the history of the field of artificial
intelligence that every time somebody figured out how to make a computer
do something—play good checkers, solve simple but relatively informal
problems—there was a chorus of critics to say, 'that's not thinking'." Researcher Rodney Brooks complains: "Every time we figure out a piece of it, it stops being magical; we say, 'Oh, that's just a computation.'"
Definition
"The
AI effect" refers to a phenomenon where either the definition of AI or
the concept of intelligence is adjusted to exclude capabilities that AI
systems have mastered. This often manifests as tasks that AI can now
perform successfully no longer being considered part of AI, or as the
notion of intelligence itself being redefined to exclude AI
achievements. Edward Geist credits John McCarthy for coining the term "AI effect" to describe this phenomenon.
McCorduck calls it an "odd paradox" that "practical AI successes,
computational programs that actually achieved intelligent behavior were
soon assimilated into whatever application domain they were found to be
useful in, and became silent partners alongside other problem-solving
approaches, which left AI researchers to deal only with the 'failures',
the tough nuts that couldn't yet be cracked." It is an example of moving the goalposts.
When problems have not yet been formalised, they can still be characterised by a model of computation that includes human computation.
The computational burden of a problem is split between a computer and a
human: one part is solved by computer and the other part solved by a
human. This formalisation is referred to as a human-assisted Turing machine.
AI applications become mainstream
Software and algorithms developed by AI researchers are now
integrated into many applications throughout the world, without really
being called AI. This underappreciation is known from such diverse
fields as computer chess, marketing, agricultural automation and hospitality.
Michael Swaine
reports "AI advances are not trumpeted as artificial intelligence so
much these days, but are often seen as advances in some other field".
"AI has become more important as it has become less conspicuous", Patrick Winston
says. "These days, it is hard to find a big system that does not work,
in part, because of ideas developed or matured in the AI world."
According to Stottler Henke,
"The great practical benefits of AI applications and even the existence
of AI in many software products go largely unnoticed by many despite
the already widespread use of AI techniques in software. This is the AI
effect. Many marketing people don't use the term 'artificial
intelligence' even when their company's products rely on some AI
techniques. Why not?"
Marvin Minsky
writes "This paradox resulted from the fact that whenever an AI
research project made a useful new discovery, that product usually
quickly spun off to form a new scientific or commercial specialty with
its own distinctive name. These changes in name led outsiders to ask,
Why do we see so little progress in the central field of artificial
intelligence?"
Nick Bostrom
observes that "A lot of cutting edge AI has filtered into general
applications, often without being called AI because once something
becomes useful enough and common enough it's not labelled AI anymore."
To avoid the AI effect problem, the editors of a special issue of IEEE Software on AI and software engineering recommend not overselling – not hyping – the real achievable results to start with.
The Bulletin of the Atomic Scientists organization views the AI effect as a worldwide strategic military threat. They point out that it obscures the fact that applications of AI had already found their way into both US and Soviet militaries during the Cold War.
AI tools to advise humans regarding weapons deployment were developed
by both sides and received very limited usage during that time.
They believe this constantly shifting failure to recognise AI continues
to undermine human recognition of security threats in the present day.
Some experts think that the AI effect will continue, with
advances in AI continually producing objections and redefinitions of
public expectations. Some also believe that the AI effect will expand to include the dismissal of specialised artificial intelligences.
In the early 1990s, during the second "AI winter" many AI researchers
found that they could get more funding and sell more software if they
avoided the bad name of "artificial intelligence" and instead pretended
their work had nothing to do with intelligence at all.
Patty Tascarella wrote in 2006: "Some believe the word 'robotics'
actually carries a stigma that hurts a company's chances at funding."
Saving a place for humanity at the top of the chain of being
Michael Kearns suggests that "people subconsciously are trying to preserve for themselves some special role in the universe".
By discounting artificial intelligence people can continue to feel
unique and special. Kearns argues that the change in perception known as
the AI effect can be traced to the mystery being removed from
the system. In being able to trace the cause of events implies that it's
a form of automation rather than intelligence.
A related effect has been noted in the history of animal cognition and in consciousness studies, where every time a capacity formerly thought of as uniquely human is discovered in animals (e.g. the ability to make tools, or passing the mirror test), the overall importance of that capacity is deprecated.
Herbert A. Simon,
when asked about the lack of AI's press coverage at the time, said,
"What made AI different was that the very idea of it arouses a real fear
and hostility in some human breasts. So you are getting very strong
emotional reactions. But that's okay. We'll live with that."
Mueller 1987 proposed comparing AI to human intelligence, coining the standard of Human-Level Machine Intelligence.This nonetheless suffers from the AI effect however when different humans are used as the standard.
Deep Blue defeats Kasparov
When IBM's chess-playing computer Deep Blue succeeded in defeating Garry Kasparov in 1997, public perception of chess playing shifted from a difficult mental task to a routine operation.
The public complained that Deep Blue had only used "brute force methods" and it wasn't real intelligence. Notably, John McCarthy,
an AI pioneer and founder of the term "artificial intelligence", was
disappointed by Deep Blue. He described it as a mere brute force machine
that did not have any deep understanding of the game. McCarthy would
also criticize how widespread the AI effect is ("As soon as it works, no
one calls it AI anymore"), but in this case did not think that Deep Blue was a good example.
A problem that proponents of AI
regularly face is this: When we know how a machine does something
"intelligent", it ceases to be regarded as intelligent. If I beat the
world's chess champion, I'd be regarded as highly bright.
STM image of self-assembled Br4-pyrene molecules on Au(111) surface (top) and its model (bottom; pink spheres are Br atoms).
Self-assembly is a process in which a disordered system of
pre-existing components forms an organized structure or pattern as a
consequence of specific, local interactions among the components
themselves, without external direction. When the constitutive components
are molecules, the process is termed molecular self-assembly.
Self-assembly can be classified as either static or dynamic. In static self-assembly, the ordered state forms as a system approaches equilibrium, reducing its free energy. However, in dynamic
self-assembly, patterns of pre-existing components organized by
specific local interactions are not commonly described as
"self-assembled" by scientists in the associated disciplines. These
structures are better described as "self-organized", although these terms are often used interchangeably.
In chemistry and materials science
Self-assembly in the classic sense can be defined as the spontaneous and reversible organization of molecular units into ordered structures by non-covalent interactions. The first property of a self-assembled system that this definition suggests is the spontaneity
of the self-assembly process: the interactions responsible for the
formation of the self-assembled system act on a strictly local level—in
other words, the nanostructure builds itself.
Although self-assembly typically occurs between
weakly-interacting species, this organization may be transferred into
strongly-bound covalent systems. An example for this may be observed in the self-assembly of polyoxometalates. Evidence suggests that such molecules assemble via a dense-phase type mechanism whereby small oxometalate ions first assemble non-covalently in solution, followed by a condensation reaction that covalently binds the assembled units. This process can be aided by the introduction of templating agents to control the formed species. In such a way, highly organized covalent molecules may be formed in a specific manner.
Self-assembled nano-structure is an object that appears as a
result of ordering and aggregation of individual nano-scale objects
guided by some physical principle.
A particularly counter-intuitive example of a physical principle that can drive self-assembly is entropy maximization. Though entropy is conventionally associated with disorder, under suitable conditions entropy can drive nano-scale objects to self-assemble into target structures in a controllable way.
Another important class of self-assembly is field-directed
assembly. An example of this is the phenomenon of electrostatic
trapping. In this case an electric field
is applied between two metallic nano-electrodes. The particles present
in the environment are polarized by the applied electric field. Because
of dipole interaction with the electric field gradient the particles are
attracted to the gap between the electrodes.
Generalizations of this type approach involving different types of
fields, e.g., using magnetic fields, using capillary interactions for
particles trapped at interfaces, elastic interactions for particles
suspended in liquid crystals have also been reported.
Regardless of the mechanism driving self-assembly, people take
self-assembly approaches to materials synthesis to avoid the problem of
having to construct materials one building block at a time. Avoiding
one-at-a-time approaches is important because the amount of time
required to place building blocks into a target structure is
prohibitively difficult for structures that have macroscopic size.
Once materials of macroscopic size can be self-assembled, those
materials can find use in many applications. For example,
nano-structures such as nano-vacuum gaps are used for storing energy[9] and nuclear energy conversion. Self-assembled tunable materials are promising candidates for large surface area electrodes in batteries and organic photovoltaic cells, as well as for microfluidic sensors and filters.
Distinctive features
At this point, one may argue that any chemical reaction driving atoms and molecules to assemble into larger structures, such as precipitation,
could fall into the category of self-assembly. However, there are at
least three distinctive features that make self-assembly a distinct
concept.
Order
First, the self-assembled structure must have a higher order
than the isolated components, be it a shape or a particular task that
the self-assembled entity may perform. This is generally not true in chemical reactions, where an ordered state may proceed towards a disordered state depending on thermodynamic parameters.
Interactions
The second important aspect of self-assembly is the predominant role of weak interactions (e.g. Van der Waals, capillary, , hydrogen bonds, or entropic forces) compared to more "traditional" covalent, ionic, or metallic bonds. These weak interactions are important in materials synthesis for two reasons.
First, weak interactions take a prominent place in materials,
especially in biological systems. For instance, they determine the
physical properties of liquids, the solubility of solids, and the organization of molecules in biological membranes.
Second, in addition to the strength of the interactions,
interactions with varying degrees of specificity can control
self-assembly. Self-assembly that is mediated by DNA pairing
interactions constitutes the interactions of the highest specificity
that have been used to drive self-assembly. At the other extreme, the least specific interactions are possibly those provided by
emergent forces that arise from entropy maximization.
Building blocks
The
third distinctive feature of self-assembly is that the building blocks
are not only atoms and molecules, but span a wide range of nano- and mesoscopic structures, with different chemical compositions, functionalities, and shapes. Research into possible three-dimensional shapes of self-assembling micrites examines Platonic solids (regular polyhedral). The term 'micrite' was created by DARPA to refer to sub-millimeter sized microrobots, whose self-organizing abilities may be compared with those of slime mold. Recent examples of novel building blocks include polyhedra and patchy particles. Examples also included microparticles with complex geometries, such as hemispherical, dimer, discs,
rods, molecules, as well as multimers. These nanoscale building blocks
can in turn be synthesized through conventional chemical routes or by
other self-assembly strategies such as directional entropic forces.
More recently, inverse design approaches have appeared where it is
possible to fix a target self-assembled behavior, and determine an
appropriate building block that will realize that behavior.
Thermodynamics and kinetics
Self-assembly
in microscopic systems usually starts from diffusion, followed by the
nucleation of seeds, subsequent growth of the seeds, and ends at Ostwald ripening. The thermodynamic driving free energy can be either enthalpic or entropic or both. In either the enthalpic or entropic case, self-assembly proceeds through the formation and breaking of bonds, possibly with non-traditional forms of mediation.
The kinetics of the self-assembly process is usually related to diffusion, for which the absorption/adsorption rate often follows a Langmuir adsorption model which in the diffusion controlled concentration (relatively diluted solution) can be estimated by the Fick's laws of diffusion. The desorption rate is determined by the bond strength of the surface molecules/atoms with a thermal activation energy barrier. The growth rate is the competition between these two processes.
Examples
Important examples of self-assembly in materials science include the formation of molecular crystals, colloids, lipid bilayers, phase-separated polymers, and self-assembled monolayers. The folding of polypeptide chains into proteins and the folding of
nucleic acids into their functional forms are examples of self-assembled
biological structures. Recently, the three-dimensional macroporous
structure was prepared via self-assembly of diphenylalanine derivative
under cryoconditions, the obtained material can find the application in
the field of regenerative medicine or drug delivery system. P. Chen et al. demonstrated a microscale self-assembly method using the air-liquid interface established by Faraday wave
as a template. This self-assembly method can be used for generation of
diverse sets of symmetrical and periodic patterns from microscale
materials such as hydrogels, cells, and cell spheroids.
Yasuga et al. demonstrated how fluid interfacial energy drives the
emergence of three-dimensional periodic structures in micropillar
scaffolds.
Myllymäki et al. demonstrated the formation of micelles, that undergo a
change in morphology to fibers and eventually to spheres, all
controlled by solvent change.
Properties
Self-assembly extends the scope of chemistry aiming at synthesizing
products with order and functionality properties, extending chemical
bonds to weak interactions and encompassing the self-assembly of
nanoscale building blocks at all length scales.
In covalent synthesis and polymerization, the scientist links atoms
together in any desired conformation, which does not necessarily have to
be the energetically most favoured position; self-assembling molecules,
on the other hand, adopt a structure at the thermodynamic minimum,
finding the best combination of interactions between subunits but not
forming covalent bonds between them. In self-assembling structures, the
scientist must predict this minimum, not merely place the atoms in the
location desired.
Another characteristic common to nearly all self-assembled systems is their thermodynamic stability. For self-assembly to take place without intervention of external forces, the process must lead to a lower Gibbs free energy,
thus self-assembled structures are thermodynamically more stable than
the single, unassembled components. A direct consequence is the general
tendency of self-assembled structures to be relatively free of defects.
An example is the formation of two-dimensional superlattices composed of an orderly arrangement of micrometre-sized polymethylmethacrylate
(PMMA) spheres, starting from a solution containing the microspheres,
in which the solvent is allowed to evaporate slowly in suitable
conditions. In this case, the driving force is capillary interaction,
which originates from the deformation of the surface of a liquid caused
by the presence of floating or submerged particles.
These two properties—weak interactions and thermodynamic
stability—can be recalled to rationalise another property often found in
self-assembled systems: the sensitivity to perturbations exerted
by the external environment. These are small fluctuations that alter
thermodynamic variables that might lead to marked changes in the
structure and even compromise it, either during or after self-assembly.
The weak nature of interactions is responsible for the flexibility of
the architecture and allows for rearrangements of the structure in the
direction determined by thermodynamics. If fluctuations bring the
thermodynamic variables back to the starting condition, the structure is
likely to go back to its initial configuration. This leads us to
identify one more property of self-assembly, which is generally not
observed in materials synthesized by other techniques: reversibility.
Self-assembly is a process which is easily influenced by external
parameters. This feature can make synthesis rather complex because of
the need to control many free parameters. Yet self-assembly has the
advantage that a large variety of shapes and functions on many length
scales can be obtained.
The fundamental condition needed for nanoscale building blocks to
self-assemble into an ordered structure is the simultaneous presence of
long-range repulsive and short-range attractive forces.
By choosing precursors
with suitable physicochemical properties, it is possible to exert a
fine control on the formation processes that produce complex structures.
Clearly, the most important tool when it comes to designing a synthesis
strategy for a material, is the knowledge of the chemistry of the
building units. For example, it was demonstrated that it was possible to
use diblock copolymers with different block reactivities in order to selectively embed maghemite nanoparticles and generate periodic materials with potential use as waveguides.
In 2008 it was proposed that every self-assembly process presents
a co-assembly, which makes the former term a misnomer. This thesis is
built on the concept of mutual ordering of the self-assembling system
and its environment.
At the macroscopic scale
The
most common examples of self-assembly at the macroscopic scale can be
seen at interfaces between gases and liquids, where molecules can be
confined at the nanoscale in the vertical direction and spread over long
distances laterally. Examples of self-assembly at gas-liquid interfaces
include breath-figures, self-assembled monolayers, droplet clusters, and Langmuir–Blodgett films, while crystallization of fullerene whiskers is an example of macroscopic self-assembly in between two liquids. Another remarkable example of macroscopic self-assembly is the formation of thin quasicrystals at an air-liquid interface, which can be built up not only by inorganic, but also by organic molecular units. Furthermore, it was reported that Fmoc protected L-DOPA amino acid (Fmoc-DOPA)
can present a minimal supramolecular polymer model, displaying a
spontaneous structural transition from meta-stable spheres to fibrillar
assemblies to gel-like material and finally to single crystals.
Self-assembly processes can also be observed in systems of
macroscopic building blocks. These building blocks can be externally
propelled or self-propelled.
Since the 1950s, scientists have built self-assembly systems exhibiting
centimeter-sized components ranging from passive mechanical parts to
mobile robots.
For systems at this scale, the component design can be precisely
controlled. For some systems, the components' interaction preferences
are programmable. The self-assembly processes can be easily monitored
and analyzed by the components themselves or by external observers.
In April 2014, a 3D printed plastic was combined with a "smart material" that self-assembles in water, resulting in "4D printing".
Consistent concepts of self-organization and self-assembly
People regularly use the terms "self-organization" and "self-assembly" interchangeably. As complex system
science becomes more popular though, there is a higher need to clearly
distinguish the differences between the two mechanisms to understand
their significance in physical and biological systems. Both processes
explain how collective order develops from "dynamic small-scale
interactions".
Self-organization is a non-equilibrium process where self-assembly is a
spontaneous process that leads toward equilibrium. Self-assembly
requires components to remain essentially unchanged throughout the
process. Besides the thermodynamic difference between the two, there is
also a difference in formation. The first difference is what "encodes
the global order of the whole" in self-assembly whereas in
self-organization this initial encoding is not necessary. Another
slight contrast refers to the minimum number of units needed to make an
order. Self-organization appears to have a minimum number of units
whereas self-assembly does not. The concepts may have particular
application in connection with natural selection.
Eventually, these patterns may form one theory of pattern formation in nature.
In particular, medicinal chemistry in its most common practice—focusing on small organic molecules—encompasses synthetic organic chemistry and aspects of natural products and computational chemistry in close combination with chemical biology, enzymology and structural biology,
together aiming at the discovery and development of new therapeutic
agents. Practically speaking, it involves chemical aspects of
identification, and then systematic, thorough synthetic alteration of new chemical entities
to make them suitable for therapeutic use. It includes synthetic and
computational aspects of the study of existing drugs and agents in
development in relation to their bioactivities (biological activities
and properties), i.e., understanding their structure–activity relationships
(SAR). Pharmaceutical chemistry is focused on quality aspects of
medicines and aims to assure fitness for purpose of medicinal products.
Discovery
is the identification of novel active chemical compounds, often called
"hits", which are typically found by assay of compounds for a desired biological activity. Initial hits can come from repurposing existing agents toward a new pathologic processes, and from observations of biologic effects of new or existing natural products from bacteria, fungi, plants,
etc. In addition, hits also routinely originate from structural
observations of small molecule "fragments" bound to therapeutic targets
(enzymes, receptors, etc.), where the fragments serve as starting points
to develop more chemically complex forms by synthesis. Finally, hits
also regularly originate from en-masse testing of chemical compounds against biological targets using biochemical or chemoproteomics assays, where the compounds may be from novel synthetic chemical libraries
known to have particular properties (kinase inhibitory activity,
diversity or drug-likeness, etc.), or from historic chemical compound
collections or libraries created through combinatorial chemistry.
While a number of approaches toward the identification and development
of hits exist, the most successful techniques are based on chemical and
biological intuition developed in team environments through years of
rigorous practice aimed solely at discovering new therapeutic agents.
Further chemistry and analysis is necessary, first to identify the
"triage" compounds that do not provide series displaying suitable SAR
and chemical characteristics associated with long-term potential for
development, then to improve the remaining hit series concerning the
desired primary activity, as well as secondary activities and
physiochemical properties such that the agent will be useful when
administered in real patients. In this regard, chemical modifications
can improve the recognition and binding geometries (pharmacophores)
of the candidate compounds, and so their affinities for their targets,
as well as improving the physicochemical properties of the molecule that
underlie necessary pharmacokinetic/pharmacodynamic
(PK/PD), and toxicologic profiles (stability toward metabolic
degradation, lack of geno-, hepatic, and cardiac toxicities, etc.) such
that the chemical compound or biologic is suitable for introduction into
animal and human studies.
Process chemistry and development
The
final synthetic chemistry stages involve the production of a lead
compound in suitable quantity and quality to allow large scale animal
testing, and then human clinical trials. This involves the optimization of the synthetic route for bulk industrial production, and discovery of the most suitable drug formulation. The former of these is still the bailiwick of medicinal chemistry, the latter brings in the specialization of formulation science
(with its components of physical and polymer chemistry and materials
science). The synthetic chemistry specialization in medicinal chemistry
aimed at adaptation and optimization of the synthetic route for
industrial scale syntheses of hundreds of kilograms or more is termed process synthesis,
and involves thorough knowledge of acceptable synthetic practice in the
context of large scale reactions (reaction thermodynamics, economics,
safety, etc.). Critical at this stage is the transition to more
stringent GMP requirements for material sourcing, handling, and chemistry.
Synthetic analysis
The synthetic methodology employed in medicinal chemistry is subject to constraints that do not apply to traditional organic synthesis.
Owing to the prospect of scaling the preparation, safety is of
paramount importance. The potential toxicity of reagents affects
methodology.
Structural analysis
The
structures of pharmaceuticals are assessed in many ways, in part as a
means to predict efficacy, stability, and accessibility. Lipinski's rule of five
focus on the number of hydrogen bond donors and acceptors, number of
rotatable bonds, surface area, and lipophilicity. Other parameters by
which medicinal chemists assess or classify their compounds are:
synthetic complexity, chirality, flatness, and aromatic ring count.
Structural analysis of lead compounds is often performed through
computational methods prior to actual synthesis of the ligand(s). This
is done for a number of reasons, including but not limited to: time and
financial considerations (expenditure, etc.). Once the ligand of
interest has been synthesized in the laboratory, analysis is then
performed by traditional methods (TLC, NMR, GC/MS, and others).
Training
Medicinal chemistry is by nature an interdisciplinary science, and
practitioners have a strong background in organic chemistry, which must
eventually be coupled with a broad understanding of biological concepts
related to cellular drug targets. Scientists in medicinal chemistry work
are principally industrial scientists (but see following), working as
part of an interdisciplinary team that uses their chemistry abilities,
especially, their synthetic abilities, to use chemical principles to
design effective therapeutic agents. The length of training is intense,
with practitioners often required to attain a 4-year bachelor's degree
followed by a 4–6 year Ph.D. in organic chemistry. Most training
regimens also include a postdoctoral fellowship period of 2 or more
years after receiving a Ph.D. in chemistry, making the total length of
training range from 10 to 12 years of college education. However,
employment opportunities at the Master's level also exist in the
pharmaceutical industry, and at that and the Ph.D. level there are
further opportunities for employment in academia and government.
Graduate level programs in medicinal chemistry can be found in
traditional medicinal chemistry or pharmaceutical sciences departments,
both of which are traditionally associated with schools of pharmacy, and
in some chemistry departments. However, the majority of working
medicinal chemists have graduate degrees (MS, but especially Ph.D.) in
organic chemistry, rather than medicinal chemistry,
and the preponderance of positions are in research, where the net is
necessarily cast widest, and most broad synthetic activity occurs.
In research of small molecule therapeutics, an emphasis on
training that provides for breadth of synthetic experience and "pace" of
bench operations is clearly present (e.g., for individuals with pure
synthetic organic and natural products synthesis in Ph.D. and
post-doctoral positions, ibid.). In the medicinal chemistry specialty
areas associated with the design and synthesis of chemical libraries or
the execution of process chemistry aimed at viable commercial syntheses
(areas generally with fewer opportunities), training paths are often
much more varied (e.g., including focused training in physical organic
chemistry, library-related syntheses, etc.).
As such, most entry-level workers in medicinal chemistry,
especially in the U.S., do not have formal training in medicinal
chemistry but receive the necessary medicinal chemistry and
pharmacologic background after employment—at entry into their work in a
pharmaceutical company, where the company provides its particular
understanding or model of "medichem" training through active involvement
in practical synthesis on therapeutic projects. (The same is somewhat
true of computational medicinal chemistry specialties, but not to the
same degree as in synthetic areas.)
Medical physics
deals with the application of the concepts and methods of physics to
the prevention, diagnosis and treatment of human diseases with a
specific goal of improving human health and well-being. Since 2008, medical physics has been included as a health profession according to International Standard Classification of Occupation of the International Labour Organization.
Although medical physics may sometimes also be referred to as biomedical physics, medical biophysics, applied physics in medicine, physics applications in medical science, radiological physics or hospital radio-physics, a "medical physicist" is specifically a health professional
with specialist education and training in the concepts and techniques
of applying physics in medicine and competent to practice independently
in one or more of the subfields of medical physics. Traditionally, medical physicists are found in the following healthcare specialties: radiation oncology (also known as radiotherapy or radiation therapy), diagnostic and interventional radiology (also known as medical imaging), nuclear medicine, and radiation protection. Medical physics of radiation therapy can involve work such as dosimetry, linac quality assurance, and brachytherapy. Medical physics of diagnostic and interventional radiology involves medical imaging techniques such as magnetic resonance imaging, ultrasound, computed tomography and x-ray. Nuclear medicine will include positron emission tomography
and radionuclide therapy. However one can find Medical Physicists in
many other areas such as physiological monitoring, audiology, neurology,
neurophysiology, cardiology and others.
Medical physics departments may be found in institutions such as
universities, hospitals, and laboratories. University departments are of
two types. The first type are mainly concerned with preparing students
for a career as a hospital Medical Physicist and research focuses on
improving the practice of the profession. A second type (increasingly
called 'biomedical physics') has a much wider scope and may include
research in any applications of physics to medicine from the study of
biomolecular structure to microscopy and nanomedicine.
"Medical Physicists will contribute
to maintaining and improving the quality, safety and cost-effectiveness
of healthcare services through patient-oriented activities requiring
expert action, involvement or advice regarding the specification,
selection, acceptance testing, commissioning, quality assurance/control
and optimised clinical use of medical devices and regarding patient
risks and protection from associated physical agents (e.g., x-rays,
electromagnetic fields, laser light, radionuclides) including the
prevention of unintended or accidental exposures; all activities will be
based on current best evidence or own scientific research when the
available evidence is not sufficient. The scope includes risks to
volunteers in biomedical research, carers and comforters. The scope
often includes risks to workers and public particularly when these
impact patient risk"
This mission includes the following 11 key activities:
Scientific problem solving service: Comprehensive problem
solving service involving recognition of less than optimal performance
or optimised use of medical devices, identification and elimination of
possible causes or misuse, and confirmation that proposed solutions have
restored device performance and use to acceptable status. All
activities are to be based on current best scientific evidence or own
research when the available evidence is not sufficient.
Dosimetry measurements: Measurement of doses had by patients,
volunteers in biomedical research, carers, comforters and persons
subjected to non-medical imaging exposures (e.g., for legal or
employment purposes); selection, calibration and maintenance of
dosimetry related instrumentation; independent checking of dose related
quantities provided by dose reporting devices (including software
devices); measurement of dose related quantities required as inputs to
dose reporting or estimating devices (including software). Measurements
to be based on current recommended techniques and protocols. Includes
dosimetry of all physical agents.
Patient safety/risk management (including volunteers in biomedical
research, carers, comforters and persons subjected to non-medical
imaging exposures. Surveillance of medical devices and evaluation of
clinical protocols to ensure the ongoing protection of patients,
volunteers in biomedical research, carers, comforters and persons
subjected to non-medical imaging exposures from the deleterious effects
of physical agents in accordance with the latest published evidence or
own research when the available evidence is not sufficient. Includes the
development of risk assessment protocols.
Occupational and public safety/risk management (when there is an
impact on medical exposure or own safety). Surveillance of medical
devices and evaluation of clinical protocols with respect to protection
of workers and public when impacting the exposure of patients,
volunteers in biomedical research, carers, comforters and persons
subjected to non-medical imaging exposures or responsibility with
respect to own safety. Includes the development of risk assessment
protocols in conjunction with other experts involved in occupational /
public risks.
Clinical medical device management: Specification, selection,
acceptance testing, commissioning and quality assurance/ control of
medical devices in accordance with the latest published European or
International recommendations and the management and supervision of
associated programmes. Testing to be based on current recommended
techniques and protocols.
Clinical involvement: Carrying out, participating in and supervising
everyday radiation protection and quality control procedures to ensure
ongoing effective and optimised use of medical radiological devices and
including patient specific optimization.
Development of service quality and cost-effectiveness: Leading the
introduction of new medical radiological devices into clinical service,
the introduction of new medical physics services and participating in
the introduction/development of clinical protocols/techniques whilst
giving due attention to economic issues.
Expert consultancy: Provision of expert advice to outside clients (e.g., clinics with no in-house medical physics expertise).
Education of healthcare professionals (including medical physics
trainees: Contributing to quality healthcare professional education
through knowledge transfer activities concerning the
technical-scientific knowledge, skills and competences supporting the
clinically effective, safe, evidence-based and economical use of medical
radiological devices. Participation in the education of medical physics
students and organisation of medical physics residency programmes.
Health technology assessment (HTA): Taking responsibility for the
physics component of health technology assessments related to medical
radiological devices and /or the medical uses of radioactive
substances/sources.
Innovation: Developing new or modifying existing devices (including
software) and protocols for the solution of hitherto unresolved clinical
problems.
Medical biophysics and biomedical physics
Some
education institutions house departments or programs bearing the title
"medical biophysics" or "biomedical physics" or "applied physics in
medicine". Generally, these fall into one of two categories:
interdisciplinary departments that house biophysics, radiobiology, and medical physics under a single umbrella; and undergraduate programs that prepare students for further study in medical physics, biophysics, or medicine.
Most of the scientific concepts in bionanotechnology are derived from
other fields. Biochemical principles that are used to understand the
material properties of biological systems are central in
bionanotechnology because those same principles are to be used to create
new technologies. Material properties and applications studied in
bionanoscience include mechanical properties (e.g. deformation,
adhesion, failure), electrical/electronic (e.g. electromechanical
stimulation, capacitors, energy storage/batteries), optical (e.g. absorption, luminescence, photochemistry),
thermal (e.g. thermomutability, thermal management), biological (e.g.
how cells interact with nanomaterials, molecular flaws/defects,
biosensing, biological mechanisms such as mechanosensation), nanoscience of disease (e.g. genetic disease, cancer, organ/tissue failure), as well as computing (e.g. DNA computing) and agriculture (target delivery of pesticides, hormones and fertilizers.
Medical imaging physics is also known as diagnostic and interventional radiology physics.
Clinical (both "in-house" and "consulting") physicists typically deal with areas of testing, optimization, and quality assurance of diagnostic radiology physics areas such as radiographic X-rays, fluoroscopy, mammography, angiography, and computed tomography, as well as non-ionizing radiation modalities such as ultrasound, and MRI. They may also be engaged with radiation protection issues such as dosimetry (for staff and patients). In addition, many imaging physicists are often also involved with nuclear medicine systems, including single photon emission computed tomography (SPECT) and positron emission tomography (PET).
Sometimes, imaging physicists may be engaged in clinical areas, but for research and teaching purposes, such as quantifying intravascular ultrasound as a possible method of imaging a particular vascular object.
Nuclear medicine
is a branch of medicine that uses radiation to provide information
about the functioning of a person's specific organs or to treat disease.
The thyroid, bones, heart, liver and many other organs can be easily imaged, and disorders in their function revealed. In some cases radiation sources can be used to treat diseased organs, or tumours. Five Nobel laureates have been intimately involved with the use of radioactive tracers in medicine.
Over 10,000 hospitals worldwide use radioisotopes in medicine, and about 90% of the procedures are for diagnosis. The most common radioisotope used in diagnosis is technetium-99m, with some 30 million procedures per year, accounting for 80% of all nuclear medicine procedures worldwide.
Health physics
Health physics is also known as radiation safety or radiation protection.
Health physics is the applied physics of radiation protection for
health and health care purposes. It is the science concerned with the
recognition, evaluation, and control of health hazards to permit the
safe use and application of ionizing radiation. Health physics
professionals promote excellence in the science and practice of
radiation protection and safety.
Some
aspects of non-ionising radiation physics may be considered under
radiation protection or diagnostic imaging physics. Imaging modalities
include MRI, optical imaging and ultrasound. Safety considerations include these areas and lasers
Physiological
measurements have also been used to monitor and measure various
physiological parameters. Many physiological measurement techniques are non-invasive and can be used in conjunction with, or as an alternative to, other invasive methods. Measurement methods include electrocardiography Many of these areas may be covered by other specialities, for example medical engineering or vascular science.
Biomedicine (also referred to as Western medicine, mainstream medicine or conventional medicine) is a branch of medical science that applies biological and physiological principles to clinical practice.
Biomedicine stresses standardized, evidence-based treatment validated
through biological research, with treatment administered via formally
trained doctors, nurses, and other such licensed practitioners.
Biomedicine also can relate to many other categories in health and biological related fields. It has been the dominant system of medicine in the Western world for more than a century.
Biomedicine is based on molecular biology and combines all issues of developing molecular medicine into large-scale structural and functional relationships of the human genome, transcriptome, proteome, physiome and metabolome with the particular point of view of devising new technologies for prediction, diagnosis and therapy.
Biomedicine involves the study of (patho-) physiological processes with methods from biology and physiology. Approaches range from understanding molecular interactions to the study of the consequences at the in vivo level. These processes are studied with the particular point of view of devising new strategies for diagnosis and therapy.
Depending on the severity of the disease, biomedicine pinpoints a
problem within a patient and fixes the problem through medical
intervention. Medicine focuses on curing diseases rather than improving
one's health.
In social sciences biomedicine is described somewhat differently.
Through an anthropological lens biomedicine extends beyond the realm of
biology and scientific facts; it is a socio-cultural
system which collectively represents reality. While biomedicine is
traditionally thought to have no bias due to the evidence-based
practices, Gaines & Davis-Floyd (2004) highlight that biomedicine
itself has a cultural basis and this is because biomedicine reflects the
norms and values of its creators.
Molecular biology is the process of synthesis and regulation of a
cell's DNA, RNA, and protein. Molecular biology consists of different
techniques including Polymerase chain reaction, Gel electrophoresis, and
macromolecule blotting to manipulate DNA.
Polymerase chain reaction is done by placing a mixture of the desired DNA, DNA polymerase, primers, and nucleotide bases
into a machine. The machine heats up and cools down at various
temperatures to break the hydrogen bonds binding the DNA and allows the
nucleotide bases to be added onto the two DNA templates after it has
been separated.
Gel electrophoresis
is a technique used to identify similar DNA between two unknown samples
of DNA. This process is done by first preparing an agarose gel. This
jelly-like sheet will have wells for DNA to be poured into. An electric
current is applied so that the DNA, which is negatively charged due to
its phosphate
groups is attracted to the positive electrode. Different rows of DNA
will move at different speeds because some DNA pieces are larger than
others. Thus if two DNA samples show a similar pattern on the gel
electrophoresis, one can tell that these DNA samples match.
Macromolecule blotting
is a process performed after gel electrophoresis. An alkaline solution
is prepared in a container. A sponge is placed into the solution and an
agarose gel is placed on top of the sponge. Next, nitrocellulose paper
is placed on top of the agarose gel and a paper towels are added on top
of the nitrocellulose paper to apply pressure. The alkaline solution is
drawn upwards towards the paper towel. During this process, the DNA
denatures in the alkaline solution and is carried upwards to the
nitrocellulose paper. The paper is then placed into a plastic bag and
filled with a solution full of the DNA fragments, called the probe,
found in the desired sample of DNA. The probes anneal to the
complementary DNA of the bands already found on the nitrocellulose
sample. Afterwards, probes are washed off and the only ones present are
the ones that have annealed to complementary DNA on the paper. Next the
paper is stuck onto an x ray film. The radioactivity of the probes
creates black bands on the film, called an autoradiograph. As a result,
only similar patterns of DNA to that of the probe are present on the
film. This allows us the compare similar DNA sequences of multiple DNA
samples. The overall process results in a precise reading of
similarities in both similar and different DNA sample.
Biochemistry is the science of the chemical processes which takes
place within living organisms. Living organisms need essential elements
to survive, among which are carbon, hydrogen, nitrogen, oxygen, calcium,
and phosphorus. These elements make up the four macromolecules that
living organisms need to survive: carbohydrates, lipids, proteins, and
nucleic acids.
Carbohydrates, made up of carbon, hydrogen, and oxygen, are energy-storing molecules. The simplest carbohydrate is glucose,
C6H12O6, is used in cellular respiration to produce ATP, adenosine triphosphate, which supplies cells with energy.
Proteins
are chains of amino acids that function, among other things, to
contract skeletal muscle, as catalysts, as transport molecules, and as
storage molecules. Protein catalysts can facilitate biochemical
processes by lowering the activation energy of a reaction. Hemoglobins are also proteins, carrying oxygen to an organism's cells.
Lipids, also known as fats, are small molecules derived from biochemical subunits from either the ketoacyl or isoprene groups. Creating eight distinct categories: fatty acids, glycerolipids, glycerophospholipids, sphingolipids, saccharolipids, and polyketides (derived from condensation of ketoacyl subunits); and sterol lipids and prenol lipids (derived from condensation of isoprene
subunits). Their primary purpose is to store energy over the long term.
Due to their unique structure, lipids provide more than twice the
amount of energy that carbohydrates
do. Lipids can also be used as insulation. Moreover, lipids can be used
in hormone production to maintain a healthy hormonal balance and
provide structure to cell membranes.
Nucleic acids
are a key component of DNA, the main genetic information-storing
substance, found oftentimes in the cell nucleus, and controls the
metabolic processes of the cell. DNA consists of two complementary
antiparallel strands consisting of varying patterns of nucleotides. RNA
is a single strand of DNA, which is transcribed from DNA and used for
DNA translation, which is the process for making proteins out of RNA
sequences.