An Opening Chapter of the First Generation of Artificial Intelligence in Medicine: The First Rutgers AIM Workshop, June 1975

Abstract

SummaryThe first generation of Artificial Intelligence (AI) in Medicine methods were developed in the early 1970's drawing on insights about problem solving in AI. They developed new ways of representing structured expert knowledge about clinical and biomedical problems using causal, taxonomic, associational, rule, and frame-based models. By 1975, several prototype systems had been developed and clinically tested, and the Rutgers Research Resource on Computers in Biomedicine hosted the first in a series of workshops on AI in Medicine that helped researchers and clinicians share their ideas, demonstrate their models, and comment on the prospects for the field. These developments and the workshops themselves benefited considerably from Stanford's SUMEX-AIM pioneering experiment in biomedical computer networking. This paper focuses on discussions about issues at the intersection of medicine and artificial intelligence that took place during the presentations and panels at the First Rutgers AIM Workshop in New Brunswick, New Jersey from June 14 to 17, 1975.

History of artificial intelligence in medicine

“…Most of this time period is referred to as the "AI winter," signifying a period of reduced funding and interest and subsequently fewer significant developments. 2 Many acknowledge 2 major winters: the first in the late 1970s, driven by the perceived limitations of AI, and the second in the late 1980s extending to the early 1990s, driven by the excessive cost in developing and maintaining expert 12 Largely as a result of these collaborations, the first National Institutes of Health-sponsored AIM workshop was held at Rutgers University in 1975. 11 These events represent the initial collaborations among the pioneers in AIM.…”

Artificial Intelligence in Clinical Decision Support: Challenges for Evaluating AI and Practical Implications

“…The PROLOG language for logic programming to manage reasoning and decision-making processes with logical structures was developed in the 1960’s 12 . In the 1970’s, there was a big wave of the so called first generation of AI in medicine 13 , such as Shortliffe’s work with MYCIN 14 , Kulikowski’s individualized clinical decision models 15 , and de Dombal’s computer-aided diagnosis of acute abdominal pain 16 which incorporated newer statistical reasoning methods such as probabilistic reasoning and neural networks.…”

A Scoping Review of Artificial Intelligence Algorithms in Clinical Decision Support Systems for Internal Medicine Subspecialties

“…The MYCIN suggested possible pathogens and recommended a dosage of antibiotics based on body weight. 11,12 ML is a subset of AI defined as "the field of study that gives computers the ability to learn without being explicitly programmed" by Arthur Samuel. 13 ML algorithms have four types: supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning.…”