In artificial intelligence (AI), an expert system is a computer system emulating the decision-making ability of a human expert. Expert systems are designed to solve complex problems by reasoning through bodies of knowledge, represented mainly as if–then rules rather than through conventional procedural programming code. Expert systems were among the first truly successful forms of AI software. They were created in the 1970s and then proliferated in the 1980s, being then widely regarded as the future of AI — before the advent of successful artificial neural networks. An expert system is divided into two subsystems: 1) a knowledge base, which represents facts and rules; and 2) an inference engine, which applies the rules to the known facts to deduce new facts, and can include explaining and debugging abilities.
Medicine is the science and practice of caring for patients, managing the diagnosis, prognosis, prevention, treatment, palliation of their injury or disease, and promoting their health. Medicine encompasses a variety of health care practices evolved to maintain and restore health by the prevention and treatment of illness. Contemporary medicine applies biomedical sciences, biomedical research, genetics, and medical technology to diagnose, treat, and prevent injury and disease, typically through pharmaceuticals or surgery, but also through therapies as diverse as psychotherapy, external splints and traction, medical devices, biologics, and ionizing radiation, amongst others.
Internal medicine, also known as general internal medicine in Commonwealth nations, is a medical specialty for medical doctors focused on the prevention, diagnosis, and treatment of internal diseases in adults. Medical practitioners of internal medicine are referred to as internists, or physicians in Commonwealth nations. Internists possess specialized skills in managing patients with undifferentiated or multi-system disease processes. They provide care to both hospitalized (inpatient) and ambulatory (outpatient) patients and often contribute significantly to teaching and research. Internists are qualified physicians who have undergone postgraduate training in internal medicine, and should not be confused with "interns", a term commonly used for a medical doctor who has obtained a medical degree but does not yet have a license to practice medicine unsupervised.
Dendral was a project in artificial intelligence (AI) of the 1960s, and the computer software expert system that it produced. Its primary aim was to study hypothesis formation and discovery in science. For that, a specific task in science was chosen: help organic chemists in identifying unknown organic molecules, by analyzing their mass spectra and using knowledge of chemistry. It was done at Stanford University by Edward Feigenbaum, Bruce G. Buchanan, Joshua Lederberg, and Carl Djerassi, along with a team of highly creative research associates and students. It began in 1965 and spans approximately half the history of AI research.
MYCIN was an early backward chaining expert system that used artificial intelligence to identify bacteria causing severe infections, such as bacteremia and meningitis, and to recommend antibiotics, with the dosage adjusted for patient's body weight — the name derived from the antibiotics themselves, as many antibiotics have the suffix "-mycin". The Mycin system was also used for the diagnosis of blood clotting diseases. MYCIN was developed over five or six years in the early 1970s at Stanford University. It was written in Lisp as the doctoral dissertation of Edward Shortliffe under the direction of Bruce G. Buchanan, Stanley N. Cohen and others.
A clinical decision support system (CDSS) is a health information technology that provides clinicians, staff, patients, and other individuals with knowledge and person-specific information to help health and health care. CDSS encompasses a variety of tools to enhance decision-making in the clinical workflow. These tools include computerized alerts and reminders to care providers and patients, clinical guidelines, condition-specific order sets, focused patient data reports and summaries, documentation templates, diagnostic support, and contextually relevant reference information, among other tools. CDSSs constitute a major topic in artificial intelligence in medicine.
Dermatoscopy, also known as dermoscopy or epiluminescence microscopy, is the examination of skin lesions with a dermatoscope. It is a tool similar to a camera to allow for inspection of skin lesions unobstructed by skin surface reflections. The dermatoscope consists of a magnifier, a light source, a transparent plate and sometimes a liquid medium between the instrument and the skin. The dermatoscope is often handheld, although there are stationary cameras allowing the capture of whole body images in a single shot. When the images or video clips are digitally captured or processed, the instrument can be referred to as a digital epiluminescence dermatoscope. The image is then analyzed automatically and given a score indicating how dangerous it is. This technique is useful to dermatologists and skin cancer practitioners in distinguishing benign from malignant (cancerous) lesions, especially in the diagnosis of melanoma.
CADUCEUS was a medical expert system, an early type of recommender system - by Harry Pople of the University of Pittsburgh. Finished in the mid-1980s, it was built on the INTERNIST-1 algorithm (1972-1973). In its time, CADUCEUS was described as the "most knowledge-intensive expert system in existence". CADUCEUS eventually could diagnose up to 1000 different diseases.
As a subfield in artificial intelligence, diagnosis is concerned with the development of algorithms and techniques that are able to determine whether the behaviour of a system is correct. If the system is not functioning correctly, the algorithm should be able to determine, as accurately as possible, which part of the system is failing, and which kind of fault it is facing. The computation is based on observations, which provide information on the current behaviour.
Computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical images. Imaging techniques in X-ray, MRI, endoscopy, and ultrasound diagnostics yield a great deal of information that the radiologist or other medical professional has to analyze and evaluate comprehensively in a short time. CAD systems process digital images or videos for typical appearances and to highlight conspicuous sections, such as possible diseases, in order to offer input to support a decision taken by the professional.
Edward ("Ted") Hance Shortliffe is a Canadian-born American biomedical informatician, physician, and computer scientist. Shortliffe is a pioneer in the use of artificial intelligence in medicine. He was the principal developer of the clinical expert system MYCIN, one of the first rule-based artificial intelligence expert systems, which obtained clinical data interactively from a physician user and was used to diagnose and recommend treatment for severe infections. While never used in practice, its performance was shown to be comparable to and sometimes more accurate than that of Stanford infectious disease faculty. This spurred the development of a wide range of activity in the development of rule-based expert systems, knowledge representation, belief nets and other areas, and its design greatly influenced the subsequent development of computing in medicine.
DXplain is a Clinical decision support system (CDSS) available through the World Wide Web that assists clinicians by generating stratified diagnoses based on user input of patient signs and symptoms, laboratory results, and other clinical findings. Evidential support for each differential diagnosis is presented, along with recommended follow-up that may be conducted by the clinician to arrive at a more definitive diagnosis. The system also serves as a clinician reference with a searchable database of diseases and clinical manifestations.
Imaging informatics, also known as radiology informatics or medical imaging informatics, is a subspecialty of biomedical informatics that aims to improve the efficiency, accuracy, usability and reliability of medical imaging services within the healthcare enterprise. It is devoted to the study of how information about and contained within medical images is retrieved, analyzed, enhanced, and exchanged throughout the medical enterprise.
Medical diagnosis is the process of determining which disease or condition explains a person's symptoms and signs. It is most often referred to as a diagnosis with the medical context being implicit. The information required for a diagnosis is typically collected from a history and physical examination of the person seeking medical care. Often, one or more diagnostic procedures, such as medical tests, are also done during the process. Sometimes the posthumous diagnosis is considered a kind of medical diagnosis.
Computer-aided auscultation (CAA), or computerized assisted auscultation, is a digital form of auscultation. It includes the recording, visualization, storage, analysis and sharing of digital recordings of heart or lung sounds. The recordings are obtained using an electronic stethoscope or similarly suitable recording device. Computer-aided auscultation is designed to assist health care professionals who perform auscultation as part of their diagnostic process. Commercial CAA products are usually classified as clinical decision support systems that support medical professionals in making a diagnosis. As such they are medical devices and require certification or approval from a competent authority.
Michael David Abràmoff is an American neuroscientist, ophthalmologist, vitreoretinal surgeon, computer engineer, and entrepreneur. He is the Watzke Professor of Ophthalmology and Visual Sciences at the Roy J. and Lucille A. Carver College of Medicine at the University of Iowa.
Artificial intelligence in healthcare is the application of artificial intelligence (AI) to copy or exceed human cognition in the analysis, presentation, and understanding of complex medical and healthcare data. It can augment and exceed human capabilities by providing better ways to diagnose, treat, or prevent disease. Using AI in healthcare has the potential to improve predicting, diagnosing, and treating diseases. Through machine learning algorithms and deep learning, AI can analyze large sets of clinical data and electronic health records, and can help to diagnose diseases more quickly and accurately. In addition, AI is becoming more relevant in bringing culturally competent healthcare practices to the industry.
Shinjini Kundu is an Indian American physician and computer scientist at Washington University in St. Louis School of Medicine in St. Louis, Missouri. Her research focuses on designing artificial intelligence systems to detect diseases that may be imperceptible to humans. She was named one of Forbes 30 under 30, MIT Technology Review's 35 innovators under 35, a World Economic Forum Young Global Leader, and a winner of the Carnegie Science Award.
Joann G. Elmore is a professor of medicine at the David Geffen School of Medicine, professor of Health Policy and Management at the UCLA Fielding School of Public Health Director of the UCLA National Clinician Scholars Program, the endowed chair in Health Care Delivery for The Rosalind and Arthur Gilbert Foundation, and a practicing physician. She publishes studies on diagnostic accuracy of cancer screening and medical tests in addition to AI/machine learning, using computer-aided tools to aid in the early detection process of high-risk cancers Previously, she held faculty and leadership positions at the University of Washington, Fred Hutchinson Research Center, Group Health Research Institute, Yale University and was the Associate Director and member of the National Advisory Committee for the Robert Wood Johnson Clinical Scholars Program at Yale and University of Washington. Elmore received her medical degree from the Stanford University School of Medicine, residency training in internal medicine at Yale-New Haven Hospital, with advanced epidemiology training from the Yale School of Epidemiology and Public Health and the RWJF Clinical Scholars Program. In addition, she was a RWJF generalist physician faculty scholar. Elmore is board certified in internal medicine and serves on many national and international committees. She is Editor in Chief for Adult Primary Care at Up-To-Date and enjoys seeing patients as a primary care internist and teaching clinical medicine to students and residents.
Merative L.P., formerly IBM Watson Health, is an American medical technology company that provides products and services that help clients facilitate medical research, clinical research, real world evidence, and healthcare services, through the use of artificial intelligence, data analytics, cloud computing, and other advanced information technology. Merative is owned by Francisco Partners, an American private equity firm headquartered in San Francisco, California. In 2022, IBM divested and spun-off their Watson Health division into Merative. As of 2023, it remains a standalone company headquartered in Ann Arbor with innovation centers in Hyderabad, Bengaluru, and Chennai.
