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AI's Ascendance in Medicine: A Timeline

An illustration of a robot holding a stethoscope.

Scientists began laying the groundwork for artificial intelligence (AI) in the early 1950s and were exploring multiple AI medical applications by the 1970s. In the years since, the empowering technology has proliferated.

1950

In Computers and Intelligence, Alan Turing describes the "Turing test," designed to uncover whether computers are capable of human intelligence.  

1956

John McCarthy coins the term "artificial intelligence" as the science and engineering of building intelligent machines.

1966

"Shakey," the first robot capable of interpreting instructions, is unveiled by Stanford Research Institute. 

1971

Scientists create INTERNIST-1, which uses a powerful ranking algorithm to reach diagnoses. 

1975

The National Institutes of Health sponsor the first AI in Medicine workshop at Rutgers University.

1976

"Backward chaining" AI system MYCIN delivers suggested antibiotic treatments for potential bacterial pathogens. The Present Illness Program is introduced to help evaluate edema. 

1978

Rutgers University develops the causal-associational network model, which couples statistical pattern recognition and AI for glaucoma consultations.

1986

University of Massachusetts releases DXplain, using inputted symptoms to generate diagnoses for 500 diseases—now expanded to more than 2,600 conditions.

1989

Cedars-Sinai cardiologists debut CorSage, a clinical tool that combines AI and statistical techniques to help physicians identify heart patients who are most likely to suffer another coronary event. 

1991

The Pathology Expert Interpretative Reporting System generates pathology reports with nearly 95% diagnostic accuracy. 

2003

The Human Genome Project provides a wealth of data on the genetic basis of disease.

2007

IBM creates the open-domain question-answering system Watson. In 2011, Watson wins first place on Jeopardy and, in 2017, neurologists use it to identify RNA-binding proteins altered in ALS.

2015

Pharmabot assists in medication education for pediatric patients and caregivers. 

2017

Arterys earns Food and Drug Administration (FDA) approval for a product that analyzes heart MRIs in seconds.

2017

Deep-learning applications screen for diseases ranging from diabetic retinopathy to skin cancer with astonishing accuracy.  The FDA approves the first AI-powered device for operating-room use.

2019

The FDA approves the first AI-powered device for cancer diagnosis as well as a deep-learning algorithm for interpretation of brain MRIs.

2019

Cedars-Sinai establishes the Division of Artificial Intelligence in Medicine, led by Sumeet Chugh, MD, the Pauline and Harold Price Chair in Cardiac Electrophysiology Research, who relies on AI and population-wide data to demystify susceptibility to cardiac arrest.

2020

Google DeepMind uses AI to predict a protein’s 3D structure from its amino-acid sequence, solving one of biology’s greatest challenges. 

2021

Established under the leadership of Jason H. Moore, PhD, the Department of Computational Biomedicine bolsters Cedars-Sinai’s research-computing infrastructure.

2022

The FDA authorizes 91 AI-powered devices. One, the EchoGo Heart Failure tool, detects heart failure from a single echocardiogram. 

Read more about the promise of integrating AI into medicine in our special report: 

The Human Factor of Artificial Intelligence