Longwood Author Series presents — Digitizing Diagnosis: Medicine, Minds, and Machines in Twentieth-Century America

Join us for this hybrid conversation with the author Andrew Lea! Register at countway.info/digitizing.

Digitizing Diagnosis: Medicine, Minds, and Machines in Twentieth-Century America

by Andrew Lea 

A fascinating history of the first attempts to computerize medical diagnosis.

Beginning in the 1950s, interdisciplinary teams of physicians, engineers, mathematicians, and philosophers began to explore the possible application of a new digital technology to one of the most central, and vexed, tasks of medicine: diagnosis. In Digitizing Diagnosis, Andrew Lea examines these efforts—and the larger questions, debates, and transformations that emerged in their wake.

Andrew Lea is a historian of science and resident physician in internal medicine at Brigham and Women’s Hospital. He graduated summa cum laude from Harvard College in 2014 with a bachelor’s degree in History and Science and went on to receive his D.Phil. (Ph.D.) in History of Science and Medicine from the University of Oxford. During his doctoral studies, he was a residential fellow at the Max-Planck-Institut für Wissenschaftsgeschichte (MPIWG) in Berlin. He earned his medical degree from the Johns Hopkins University School of Medicine, where he was selected as Match Day speaker. His research explores the history of diagnosis, disease, and medical technology and has appeared in leading historical and medical journals, including Isis and the New England Journal of Medicine. His first book Digitizing Diagnosis: Medicine, Minds, and Machines in Twentieth-Century America (Johns Hopkins University Press, 2023) examines early efforts to computerize medical diagnosis and decision-making. He is working on his second book-length project, tentatively titled Up to Date: Making and Managing Medical Information since 1880, which looks at the history of reference tools in medicine, from Index Medicus and Harrison’s Principles of Internal Medicine, to UpToDate and new algorithmically mediated resources.