title: A disease-conscious method for sequential diagnosis by use of disease probabilities without assumption of symptom independence.
abstract: A method for automatic diagnosis of disease is formulated and applied to a data base of several hundred gastroenterological patients who were each known to have one of six diseases. Application of the method requires no assumptions regarding statistical independence of symptoms. Each disease is associated with its own disease-symptom function, and any order of dependence between the symptoms and each disease may be allowed for. A patient's symptoms are used to determine the value of any specified disease-symptom function. This value is then used to determine the probability that the patient has the corresponding disease. The method is applied to a sequential diagnosis of patients not contained in the initial data base. Additional symptoms are chosen according to their diagnostic value. The entire model is disease-conscious in that disease-symptom functions, disease probabilities and diagnostic values need be evaluated only for those diseases that are considered relevant to the diagnosis.
mesh_terms: D001499:Bayes Theorem; D003936:Diagnosis, Computer-Assisted; D005767:Gastrointestinal Diseases / Q000175:diagnosis; D008433:Mathematics; D011336:Probability