A computer vision system for deep learning-based detection of patient mobilization activities in the ICU
December 1, 2022ConcertAI
December 1, 20221974-1976
The years 1974-1976 witnessed the work of many scientists revolutionizing AI from Biomedical informatics to Natural language processing...
Edward “Ted” Shortliffe: was born in Canada and grew up in the United States. He is a biomedical informatician, physician, and computer scientist. Shortliffe is a pioneer in the field of medical artificial intelligence. He was the primary creator of MYCIN, one of the earliest rule-based artificial intelligence expert systems, which collected clinical data interactively from a physician user and was used to diagnose and suggest therapy for serious infections. Ted Shortliffe’s 1974 Stanford Ph.D. dissertation on the MYCIN program showed the utility of a rule-based approach to medical diagnosis, even in the face of ambiguity. Although it was never utilized in practice (since it predated local-area networking and therefore could not be integrated into patient records and physician workflow), its performance was similar to, and often superior to, that of Stanford infectious disease faculty. He is widely regarded as the father of biomedical informatics and has been instrumental in the national and international development of medicine and biomedical informatics.(1)
Edward “Ted” Shortliffe: was born in Canada and grew up in the United States. He is a biomedical informatician, physician, and computer scientist. Shortliffe is a pioneer in the field of medical artificial intelligence. He was the primary creator of MYCIN, one of the earliest rule-based artificial intelligence expert systems, which collected clinical data interactively from a physician user and was used to diagnose and suggest therapy for serious infections. Ted Shortliffe’s 1974 Stanford Ph.D. dissertation on the MYCIN program showed the utility of a rule-based approach to medical diagnosis, even in the face of ambiguity.
Although it was never utilized in practice (since it predated local-area networking and therefore could not be integrated into patient records and physician workflow), its performance was similar to, and often superior to, that of Stanford infectious disease faculty. He is widely regarded as the father of biomedical informatics and has been instrumental in the national and international development of medicine and biomedical informatics.(1)
Earl Sacerdoti : invented partial-order planning methods in 1975 for his NOAH system, replacing the old paradigm of searching among state-space descriptions. NOAH was used at SRI International to interactively diagnose and repair electromechanical systems. Earl Sacerdoti is a serial entrepreneur, management consultant, executive coach, and angel investor with a particular interest in early-stage software companies. He has almost 40 years of expertise in general management, as well as research, development, and engineering management. He has founded and developed new companies and commercialized several sophisticated software innovations. He co-founded the American Association for Artificial Intelligence and is the author of a book, as well as over 20 papers and articles on various advanced software subjects. Additionally, he is well-known for his pioneering work in the field of Artificial Intelligence.(2)
Earl Sacerdoti : invented partial-order planning methods in 1975 for his NOAH system, replacing the old paradigm of searching among state-space descriptions. NOAH was used at SRI International to interactively diagnose and repair electromechanical systems. Earl Sacerdoti is a serial entrepreneur, management consultant, executive coach, and angel investor with a particular interest in early-stage software companies. He has almost 40 years of expertise in general management, as well as research, development, and engineering management.
He has founded and developed new companies and commercialized several sophisticated software innovations. He co-founded the American Association for Artificial Intelligence and is the author of a book, as well as over 20 papers and articles on various advanced software subjects. Additionally, he is well-known for his pioneering work in the field of Artificial Intelligence.(2)
Austin Tate : is a Professor of Knowledge-based Systems at the University of Edinburgh’s School of Informatics. He is well-known for his contributions to AI planning, artificial intelligence applications, and collaborative systems in Virtual Worlds as Director of AIAI (Artificial Intelligence Applications Institute) at the previously mentioned University. Tate created the Nonlin hierarchical planning system in 1975. This system is capable of exploring incomplete plans, which are defined as alternate approaches to the plan’s underlying objective structure.(3)
Austin Tate : is a Professor of Knowledge-based Systems at the University of Edinburgh’s School of Informatics. He is well-known for his contributions to AI planning, artificial intelligence applications, and collaborative systems in Virtual Worlds as Director of AIAI (Artificial Intelligence Applications Institute) at the previously mentioned University.
Tate created the Nonlin hierarchical planning system in 1975. This system is capable of exploring incomplete plans, which are defined as alternate approaches to the plan’s underlying objective structure.(3)
Marvin Minsky released his widely read and important essay on Frames in 1975, bringing together many concepts concerning schemas and semantic connections. The frame problem is a term used in artificial intelligence to describe the difficulty in using first-order logic (FOL) to convey facts about a robot’s environment. Representing a robot’s state using conventional FOL requires the acceptance of many axioms implying that objects in the environment do not change randomly.(4)
Raj Reddy: a computer scientist, summarized the early work on Natural Language Processing in 1976 in “Speech Recognition by Machine: A Review” in Proceedings of the IEEE (Institute of Electrical and Electronics Engineers). His research in artificial intelligence has focused chiefly on the perceptual and motor aspects of intelligence, including voice, language, vision, and robotics. He is a pioneer in artificial intelligence and has taught at Stanford and Carnegie Mellon for over 50 years. He was the founding director of Carnegie Mellon University’s Robotics Institute. He was influential in the establishment of India’s Rajiv Gandhi University of Knowledge Technologies, which serves the educational requirements of low-income, talented rural youngsters. He was the first person of Asian ancestry to win the ACM Turing Award, often known as the Computer Science Nobel Prize, in 1994 for his contributions to artificial intelligence.(5)
Raj Reddy: a computer scientist, summarized the early work on Natural Language Processing in 1976 in “Speech Recognition by Machine: A Review” in Proceedings of the IEEE (Institute of Electrical and Electronics Engineers). His research in artificial intelligence has focused chiefly on the perceptual and motor aspects of intelligence, including voice, language, vision, and robotics. He is a pioneer in artificial intelligence and has taught at Stanford and Carnegie Mellon for over 50 years. He was the founding director of Carnegie Mellon University’s Robotics Institute.
He was influential in the establishment of India’s Rajiv Gandhi University of Knowledge Technologies, which serves the educational requirements of low-income, talented rural youngsters. He was the first person of Asian ancestry to win the ACM Turing Award, often known as the Computer Science Nobel Prize, in 1994 for his contributions to artificial intelligence.(5)
The creation of a consultation program for Glaucoma using the CASNET model was one of the prototypes demonstrating the possibility of using AI in medicine, developed at Rutgers University and first exhibited publicly in 1976 at the Academy of Ophthalmology’s annual conference in Las Vegas, Nevada. The CASNET is a consultant to ophthalmologists for complex cases of Glaucoma and is used as a vehicle for research in medical modeling and decision-making. This model is a causal–association network composed of three distinct programs: model construction, consultation, and a collaboratively created and maintained database. This approach may tailor information about a particular illness to an individual and offer doctors treatment recommendations.(6)