MEDIPHOR System (Monitoring and Evaluation of Drug Interactions by a Pharmacy-Oriented Reporting System) developed by Cohen, Shortliffe and colleagues at Stanford University Medical School, published as a chapter in the book, Drug interactions (1974). With 12 co-authors.

"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. It arose in the laboratory that had created the earlier Dendral expert system.

"MYCIN was never actually used in practice but research indicated that it proposed an acceptable therapy in about 69% of cases, which was better than the performance of infectious disease experts who were judged using the same criteria" (Wikipedia article on MYCIN, accessed 08-2017). See also, Shortliffe, Computer-based medical consultations: MYCIN. New York: Elsevier, 1976, and Buchanan & Shortliffe, Rule based expert systems: The Mycin experiments of the Stanford Heuristic Programming Project. Reading, MA: Addison-Wesley, 1984. Digital facsimile of this 1984 work from aitopics.org at this link.

A fourth expanded edition of this textbook, edited by Shortliffe and James J. Cimino, was published as Biomedical informatics: Computer applications in health care and biomedicine (New York: Springer, 2014).

Order of authorship in the original publication: Patel, Shortliffe, Stefanelli, Szolovits, Berthold, Bellazzi, Abu-Hanna. "Abstract: This paper is based on a panel discussion held at the Artificial Intelligence in Medicine Europe (AIME) conference in Amsterdam, The Netherlands, in July 2007. It had been more than 15 years since Edward Shortliffe gave a talk at AIME in which he characterized artificial intelligence (AI) in medicine as being in its "adolescence" (Shortliffe EH. The adolescence of AI in medicine: will the field come of age in the '90s? Artificial Intelligence in Medicine 1993;5:93-106). In this article, the discussants reflect on medical AI research during the subsequent years and characterize the maturity and influence that has been achieved to date. Participants focus on their personal areas of expertise, ranging from clinical decision-making, reasoning under uncertainty, and knowledge representation to systems integration, translational bioinformatics, and cognitive issues in both the modeling of expertise and the creation of acceptable systems."