HOME

TheInfoList



OR:

{{Short description, Computer-assisted diagnostic software tool INTERNIST-I was a broad-based computer-assisted diagnostic tool developed in the early 1970s at the
University of Pittsburgh The University of Pittsburgh (Pitt) is a public state-related research university in Pittsburgh, Pennsylvania. The university is composed of 17 undergraduate and graduate schools and colleges at its urban Pittsburgh campus, home to the universit ...
as an educational experiment. The system was designed to capture the expertise of just one man, Jack D. Myers, MD, chairman of internal medicine in the
University of Pittsburgh School of Medicine The University of Pittsburgh School of Medicine is a medical school of the University of Pittsburgh, located in Pittsburgh, Pennsylvania. The School of Medicine, also known as Pitt Med, is consistently ranked as a "Top Medical School" by '' ...
. The Division of Research Resources and the
National Library of Medicine The United States National Library of Medicine (NLM), operated by the United States federal government, is the world's largest medical library. Located in Bethesda, Maryland, the NLM is an institute within the National Institutes of Health. Its ...
funded INTERNIST-I. Other major collaborators on the project included Randolph A. Miller and Harry E. Pople.


Development

INTERNIST-I is the successor of the DIALOG system. For ten years, INTERNIST-I was the centerpiece of a Pittsburgh course entitled “The Logic of Problem-Solving in Clinical Diagnosis.” In consultation with faculty experts, much responsibility for data entry and updating of the system fell to the fourth-year medical students enrolled in the course. These students encoded the findings of standard clinicopathological reports. By 1982, the INTERNIST-I project represented fifteen person-years of work, and by some reports covered 70-80% of all the possible diagnoses in internal medicine. Data input into the system by operators included signs and symptoms, laboratory results, and other items of patient history. The principal investigators on INTERNIST-I did not follow other medical expert systems designers in adopting
Bayesian Thomas Bayes (/beɪz/; c. 1701 – 1761) was an English statistician, philosopher, and Presbyterian minister. Bayesian () refers either to a range of concepts and approaches that relate to statistical methods based on Bayes' theorem, or a followe ...
statistical models or
pattern recognition Pattern recognition is the automated recognition of patterns and regularities in data. It has applications in statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphi ...
. This was because, as Myers explained, “The method used by physicians to arrive at diagnoses requires complex information processing which bears little resemblance to the statistical manipulations of most computer-based systems.” INTERNIST-I instead used a powerful ranking algorithm to reach diagnoses in the domain of internal medicine. The heuristic rules that drove INTERNIST-I relied on a partitioning algorithm to create problems areas, and exclusion functions to eliminate diagnostic possibilities. These rules, in turn, produce a list of ranked diagnoses based on disease profiles existing in the system’s memory. When the system was unable to make a determination of diagnosis it asked questions or offered recommendations for further tests or observations to clear up the mystery. INTERNIST-I worked best when only a single disease was expressed in the patient, but handled complex cases poorly, where more than one disease was present. This was because the system exclusively relied on hierarchical or taxonomic decision-tree logic, which linked each disease profile to only one “parent” disease class.


Use of INTERNIST-I

By the late 1970s, INTERNIST-I was in experimental use as a consultant program and educational “quizmaster” at Presbyterian-University Hospital in Pittsburgh. INTERNIST-I’s designers hoped that the system could one day become useful in remote environments—rural areas, outer space, and foreign military bases, for instance—where experts were in short supply or unavailable. Still, physicians and paramedics wanting to use INTERNIST-I found the training period lengthy and the interface unwieldy. An average consultation with INTERNIST-I required about thirty to ninety minutes, too long for most clinics. To meet this challenge, researchers at nearby
Carnegie Mellon University Carnegie Mellon University (CMU) is a private research university in Pittsburgh, Pennsylvania. One of its predecessors was established in 1900 by Andrew Carnegie as the Carnegie Technical Schools; it became the Carnegie Institute of Technology ...
wrote a program called ZOG that allowed those unfamiliar with the system to master it more rapidly. INTERNIST-I never moved beyond its original status as a research tool. In one instance, for example, a failed attempt to extract “synthetic” case studies of “artificial patients” from the system’s knowledge base in the mid-1970s overtly demonstrated its “shallowness” in practice.


INTERNIST-I and QMR

In the first version of INTERNIST-I (completed in 1974) the computer program “treated the physician as unable to solve a diagnostic problem,” or as a “passive observer” who merely performed data entry. Miller and his collaborators came to see this function as a liability in the 1980s, referring to INTERNIST-I derisively as an example of the outmoded “Greek Oracle” model for medical
expert systems In artificial intelligence, 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 ...
. In the mid-1980s INTERNIST-I was succeeded by a powerful microcomputer-based consultant developed at the University of Pittsburgh called
Quick Medical Reference (QMR) Quick, as an adjective, refers to something moving with high speed. Quick may also refer to: In business * Quick (restaurant), a Belgian fast-food restaurant chain * Quick (sportswear), a Dutch manufacturer of sportswear * Quick (automobile) ...
. QMR, meant to rectify the technical and philosophical deficiencies of INTERNIST-I, still remained dependent on many of the same algorithms developed for INTERNIST-I, and the systems are often referred to together as INTERNIST-I/QMR. The main competitors to INTERNIST-I included CASNET, MYCIN, and PIP.


See also

*
CADUCEUS (expert system) CADUCEUS was a medical expert system finished in the mid-1980s (first begun in the 1970s- it took a long time to build the knowledge base) by Harry Pople (of the University of Pittsburgh), building on Pople's years of interviews with Dr. Jack Meye ...


References

*Gregory Freiherr, The Seeds of Artificial Intelligence: SUMEX-AIM (NIH Publication 80-2071, Washington, D.C.: National Institutes of Health, Division of Research Resources, 1979). *Randolph A. Miller, et al., “INTERNIST-1: An Experimental Computer-Based Diagnostic Consultant for General Internal Medicine,” New England Journal of Medicine 307 (August 19, 1982): 468-76. *Jack D. Myers, “The Background of INTERNIST-I and QMR,” in A History of Medical Informatics, eds. Bruce I. Blum and Karen Duncan (New York: ACM Press, 1990), 427-33. *Jack D. Myers, et al., “INTERNIST: Can Artificial Intelligence Help?” in Clinical Decisions and Laboratory Use, eds. Donald P. Connelly, et al., (Minneapolis: University of Minnesota Press, 1982), 251-69. *Harry E. Pople, Jr., “Presentation of the INTERNIST System,” in Proceedings of the AIM Workshop (New Brunswick, N.J.: Rutgers University, 1976). *D. A. Wolfram, "An appraisal of INTERNIST-I," Artificial Intelligence in Medicine, 7, 2 (1995) 93–116
doi.org/10.1016/0933-3657(94)00028-Q
h1>

External links



Medical expert systems Expert systems Medical software