An intelligent multimodal medical diagnosis system based on patients’ medical questions and structured symptoms for telemedicine

Agent-based intelligent medical diagnosis system for patients.

BACKGROUND According to the analysis of the challenges faced by the current public health circumstances such as the sharp increase in elderly patients, limited medical personnel, resources and technology, the agent-based intelligent medical diagnosis system for patients (AIMDS) is proposed in this research. OBJECTIVE Based on advanced sensing technology and professional medical knowledge, the...

Medical Knowledge-Based System for Diagnosis from Symptoms and Signs

This research proposes design and development of a medical knowledge-based system (MKBS) for diagnosis from symptoms and signs. This system was developed to support a knowledge construction and an inference engine. The knowledge construction was based on a concept of production rules, which was performed in tree structure. The inference engine used interactive forward chaining technique to infe...

Modelling Intelligent System for Medical Diagnosis

An Intelligent Method for Compression of Medical Images in Telemedicine

The medical images can be transmitted from patient room to remote medical centers for diagnosis through the wireless network in telemedicine system. In this connection, the existing methods are unable to achieve better Compression Ratio (CR) while maintaining the lower levels of distortion. An intelligent scheme has been developed for achieving a higher compression ratio and low distortion rate...

CMDTS: The Causality-based Medical Diagnosis and Treatment System

Our medical world is replete with clinical data but this data is rarely automatically exploited for bringing more health to our society. Many researches have been conducted in Medical Data Mining, but almost all of them have focused on diagnosing the diseases not treating the patients. In this paper we propose the Causality-based Medical Diagnosis and Treatment System, which can be used to diag...