Acquiring patient data by an intelligent interface agent with medicine-related common sense reasoning

Abstract

The first process in medical diagnosis is gathering useful patient data from physical examination. How to capture proper and correct morbidity during a consultation is a very difficult task. It usually takes many years of clinical training and practice for a physician to successfully do this. This paper proposes an intelligent interface agent to alleviate the problem. It includes an hypermedia human–machine interface, a medicine-related common sense and past Q&A scenarios repository, and a data analyst. The hypermedia interface provides a friendly human body image for easy patient data input. The data analyst, with the help of medicine-related common sense and past Q&A scenarios, supports the determination of proficiency level of the user; verification of completeness, consistency, and rationality of the input data; and generation of complete patient data. Knowing the proficiency level of a user facilitates the system in soliciting relevant patient's data. Verification of the input data against the common sense allows the system to guarantee their validity. Generation of complete patient data is carried out by hypothesizing a major disease using the common sense, followed by producing more diseases through the interaction of the involved symptoms, and completed by adding those symptoms that are decided to be significant in the discovered diseases into the patient record. The intelligent system thus can correctly gather high-quality patient data from all user levels.