A mathematical approach to medical decisions: Application of Bayes' rule to a mixture of continuous and discrete clinical variables

✍ Scribed by C.Frank Starmer; K.L. Lee

• Publisher: Elsevier Science
• Year: 1976
• Tongue: English
• Weight: 634 KB
• Volume: 9
• Category: Article
• ISSN: 0010-4809
• DOI: 10.1016/0010-4809(76)90012-4

✦ Synopsis

Conditional probability formulations have frequently been used to form decision models relating disease probabilities to a set of descriptors or symptoms. The formulations have usually assumed the symptoms to be either all discrete-valued or all continuously valued. A mixed-data model (for both continuously valued and discrete valued symptoms) is presented and shown to represent a general class of models of which nonmixed-data models are special cases. By testing independence of symptoms prior to developing the decision model, one can take advantage of a potential reduction in the number of parameters that must be estimated.