{"type":"ScholarlyArticle","title":"Causal Understanding of Patient Illness in Medical Diagnosis","authors":[{"name":"Ramesh S. Patil","slug":"ramesh-s-patil","given":"Ramesh S.","family":"Patil","affiliation":""},{"name":"Peter Szolovits","slug":"peter-szolovits","given":"Peter","family":"Szolovits","affiliation":""},{"name":"William B. Schwartz","slug":"william-b-schwartz","given":"William B.","family":"Schwartz","affiliation":""}],"abstract":"First generati on AI in Med ic ine programs have clearl y demonstrated the usefulness of Alte chnique s. However . it h as al so bee n recog niz ~ d that the use of noti ons su ch as causal relationships . temporal patterns. ond aggregate disease categories in these programs has been too weak . From our study of clinician's behavior we reali1.ed that a diagno stic or therapeutic program must consider a case at various lev els of detail to integrate overall understanding with detailed knowledge . To explore these issues. we have undertaken a study of tht problem of providing expert consultation for electrolyte and acid-base disturbances. We have partly completed an implementation of ABEL. the diagnostic compo nent of the overall effort. In this paper we wncentrate on AUU .' s mechanism for de,crihing a patient. Called the patient -specific model, this description indudes data about the patient as well as the program's hypothetical interpretations of these data in a multi-level causal network . The lowes[ level of this description consists of pathophysiological knowledge about the patient. which is successively aggregated into higher level concepts and relations. gradually shifting the content from pathophysiological lo syndromic knowledge . The aggregate level of this description summarize!' the patient data providing a glob;~ perspective for efficient exploration of the diagnostic possi· bil itie s. Th~ pathophysiological level description provides the ability to handle complex clinical situations arising in illnesses with multiple etiologies, to evalu;lle the physiological validity of diagnostic pos sibilities being explored, and to organize large amounts of seemingly unrelated facts into coherent causal descriptions.","doi":null,"url":"https://ijcai.org/proceedings/1981/170","pdf":"https://ijcai.org/proceedings/1981/0170.pdf","markdown":"https://ijcai.org/proceedings/1981/170.md","bibtex":"https://ijcai.org/proceedings/1981/bibtex/170","volume":{"slug":"1981","title":"Proceedings of the Seventh International Joint Conference on Artificial Intelligence","short_title":"IJCAI 1981","url":"https://ijcai.org/proceedings/1981/","year":1981,"location":"Vancouver, British Columbia, Canada","dates":"24-28 August 1981","editors":"Roger C. Schank","isbn":"","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Medical Application","track":"Medical Application","number":170,"pages":{"first":893,"last":898},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}