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lecture10 notes

# lecture10 notes - Decision Analysis Decision Support...

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Decision Analysis & Decision Support 6.872/HST.950

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Types of Decision Support “Doctor's Assistant” for clinicians at any level of training Expert (specialist) consultation for non- specialists Monitoring and error detection Critiquing, what-if Guiding patient-controlled care Education and Training Contribution to medical research

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Two Historical Views on How to Build Expert Systems Great cleverness Powerful inference abilities Ab initio reasoning Great stores of knowledge Possibly limited ability to infer, but Vast storehouse of relevant knowledge, indexed in an easy-to-apply form
Change over 30 years 1970’s: human knowledge, not much data 2000’s: vast amounts of data, traditional human knowledge (somewhat) in doubt Could we “re-discover” all of medicine from data? I think not! Should we focus on methods for reasoning with uncertain data? Absolutely! But: Feinstein, A. R. (1977). “Clinical Biostatistics XXXIX. The Haze of Bayes, the Aerial Palaces of Decision Analysis, and the Computerized Ouija Board.” Clinical Pharmacology and Therapeutics 21 : 482-496.

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Cancer Test We discover a cheap, 95% accurate test for cancer. Give it to “Mrs. Jones”, the next person who walks by 77 Mass Ave. Result is positive. What is the probability that Mrs. Jones has cancer?
Figuring out Cancer Probability Assume Ca in 1% of general population: + 950 1,000 Ca 95% - 50 100,000 + 4,950 99,000 95% - 94,050

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At the Extremes • If Ca probability in population is 0.1%, – Then post positive result, p(Ca)=1.87% • If Ca probability in population is 50%, – Then post-positive result, p(Ca)=95%
Bayes’ Rule + + - -

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Odds/Likelihood Form
DeDombal, et al. Experience 1970’s & 80’s • “Idiot Bayes” for appendicitis • 1. Based on expert estimates -- lousy • 2. Statistics -- better than docs • 3. Different hospital -- lousy again • 4. Retrained on local statistics -- good

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Rationality Behavior is a continued sequence of choices, interspersed by the world’s responses Best action is to make the choice with the greatest expected value … decision analysis
Example: Gangrene From Pauker’s “Decision Analysis Service” at New England Medical Center Hospital, late 1970’s. Man with gangrene of foot Choose to amputate foot or treat medically If medical treatment fails, patient may die or may have to amputate whole leg.

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