Symptomat is a medical diagnostics program that finds links between patient's complaints and diagnoses. The Diagnostic Robot is designed to ask several thousands questions. The artificial logic behind the machine compares answers with known medical knowledge. The robot analyzes all information gathered about the symptoms and compares responses to the values described by doctors. Then, it produces a list of all possible conditions matching the symptoms.
This program-robot is designed to give the list of the most probable diagnoses. It uses an artificial intelligence to give answers based on your questions. Patient sees the list of possible diagnosis and chosen options on the screen. He may print complaints and show to a medical provider. There is two-step evaluation system.
Advanced third section has more focused questions.
This broad-based computer-assisted diagnostic tool was developed in the 2006 at the University of Gulam Khan as an educational experiment. The system was designed to capture the expertise of the team of doctors, lead by Aleksandr Kavokin, MD, PhD. The Division of Research Resources and the University funded Symptomat. Other major collaborators on the project included Oleg Kavokin, MD, Alexey Kavokin, PhD *.
Development of Symptomat
For two years, Symptomat was the centerpiece of the Univesity course entitled “The Logic of Problem-Solving in Clinical Diagnosis.” Faculty experts encoded the findings of standard clinicoal questionnaires, lisitng possible diagnoses in internal medicine and surgery.
Data input into the system by operators included signs and symptoms, laboratory results, and other items of patient history. Symptomat uses a powerful ranking algorithm to reach diagnoses in the domain of medicine. The heuristic rules that drove Symptomat relied on a partitioning algorithm to create problems areas, and exclusion functions to eliminate diagnostic possibilities.
These rules, in turn, produce a list of ranked diagnoses based on disease profiles existing in the system’s memory.
Use of Symptomat
By the 2006, Symptomat was in experimental use as a consultant program and educational tool and went on-line. Symptomat designers hope that the system could one day become useful in remote environments—rural areas, where experts are in short supply or unavailable.
INTERNIST-I was a broad-based computer-assisted diagnostic tool developed in the early 1970s at the University of Pittsburgh as an educational experiment. The system was designed to capture the expertise of just one man, Jack D. Myers, MD, chairman of internal medicine in the Pittsburgh School of Medicine. The Division of Research Resources and the National Library of Medicine funded INTERNIST-I. Other major collaborators on the project included Randolph A. Miller, Harry E. Pople, and Victor Yu.