Paper page: bmcmedresmethodol.biomedcentral.com/articles/10.1186/s12874-019-0681-4#citeas
“Following visible successes on a wide range of predictive tasks, machine learning techniques are attracting substantial interest from medical researchers and clinicians. We address the need for capacity development in this area by providing a conceptual introduction to machine learning alongside a practical guide to developing and evaluating predictive algorithms using freely-available open source software and public domain data”.
Chris Sidey-Gibbons. Department of Symptom Research, Division of Internal Medicine. (Source: faculty.mdanderson.org/profiles/christopher_gibbons.html).
Dr. Sidey-Gibbons. Holds an honors bachelor’s degree in mechanical engineering from McGill University in Montreal, Quebec (2011). While at McGill, she conducted research on flame propagation in microgravity in collaboration with the Canadian Space Agency (CSA) and the National Research Council Flight Research Laboratory. (Source: asc-csa.gc.ca/eng/astronauts/canadian/active/bio-jennifer-sidey.asp).