A holonic multi-agent based diagnostic decision support system for computer-aided history and physical examination

Abstract

Available Medical Diagnosis systems (MDSs), including the state of the art, mainly focus on finding the perfect link between the patient’s medical history and their health knowledge. However, no matter how powerful they are in performing this action, it is always possible that the final strong deduction is based on some incomplete input. Prior to this process, a physician should literally perform the Differential Diagnosis (DDx), in which (S)he carefully listens to the symptoms explained by the patient, considers some potential diagnoses and then tries to gather enough evidence and supporting information to shrink the probability of the other candidates. In a patient encounter, this method is used in a process called the History and Physical examination (H&P). Only physicians and in some institutions, in order to compensate the shortage of the physicians, some specially trained nurses are qualified to perform this process. A system capable of guiding a focus H&P, however, will allow less experienced nurses to perform this process, and furthermore, can provide second opinions in critical cases. The DDx domain is in fact a holonic domain; hence, a MDS with holonic architecture could be able to perform this process. As the Holonic Medical Diagnosis System (HMDS), tends to cover the stages in the H&P, this system could also be added to available MDSs in order to provide them with the essential comprehensive input and allow their integration in the clinical workflow. This paper will demonstrate the performance of this system and concentrates on its learning process.