You'll have to figure this one out for yourselves.

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Estimated differences: Adjusted mortality: 11.07% Regarding the number of regression parameters: Not explicitly listed, but by the following paragraph, I would suspect there are at least hundreds of regression parameters (such as an indicator of medical of school attended). "We accounted for patient characteristics, physician characteristics, and hospital fixed effects. Patient characteristics included patient age in 5-year increments (the oldest group was categorized as 95 years), sex, race/ethnicity (non-Hispanic white, non-Hispanic black, Hispanic, and other), primary diagnosis (Medicare Severity Diagnosis Related Group), 27 coexisting conditions (determined using the Elixhauser comorbidity index28), median annual household income estimated from residential zip codes (in deciles), an indicator variable for Medicaid coverage, and indicator variables for year. Physician characteristics included physician age in 5-year increments (the oldest group was categorized as 70 years), indicator variables for the medical schools from which the physicians graduated, and type of medical training (ie, allopathic vs osteopathic29 training)."


Artificial Intelligence And Deep Learning Are On The Business School Syllabus

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In a Harvard Business School classroom in Boston, MA, robots are on the rise. MBA students are trying to crack a case study on the self-driving cars pioneered by Tesla, Google, and Uber. What is the potential for robots to reshape our roads? And what are the challenges and opportunities of entering that business? This is a case that David Yoffie, professor of international business administration, believes is essential reading for tomorrow's business leaders.


The Best AI Still Flunks 8th Grade Science

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In 2012, IBM Watson went to medical school. So said The New York Times, announcing that the tech giant's artificially intelligent question-and-answer machine had begun a "stint as a medical student" at the Cleveland Clinic Lerner College of Medicine. This was just a metaphor. Clinicians were helping IBM train Watson for use in medical research. But as metaphors go, it wasn't a very good one.


AI for the M.D

Science

Freed from a variety of tasks by artificial intelligence, doctors will have more time with patients, Topol predicts. In 1970 in The New England Journal of Medicine, William Schwartz predicted that by the year 2000, much of the intellectual function of medicine could be either taken over or at least substantially augmented by "expert systems"--a branch of artificial intelligence (AI). Schwartz hoped that the medical school curriculum would be "redirected toward the social and psychologic aspects of health care" and that medical schools would attract applicants interested in "behavioral and social sciences and … the information sciences and their application to medicine." But Schwartz's dream of smart medical technologies, for the most part, remains just that. Eric Topol, however, is optimistic about the future of health care.


Case-based Reasoning for the Case Method

AAAI Conferences

Eighty-five years ago, Harvard created a business school to train the leaders of industry and commerce. Within a decade, Harvard had institutionalized case study as its primary teaching method in the business school. Today, the case method is a fixture at most business schools. An average MBA student prepares (or is supposed to prepare) up to 600 cases during his or her two years in graduate school. The contrasts between the case method and traditional teaching methods are similar to those between case-based reasoning and rule-based systems.