Artificial Cognition-based Medical Diagnosis and Treatment Recommendation System: A Review

Abstract

In our rapidly evolving world, technological advancements and innovations have led to increasingly complex mechanisms. This research paper presents the implementation of an artificial cognition-based medical diagnosis and treatment recommendation system. The aim of the study is to leverage technological advancements in natural language processing, wearable devices, and image analysis to create a sophisticated system capable of accurately and efficiently diagnosing diseases and suggesting appropriate medical treatments. The methodology draws inspiration from IBM's Watson model and integrates cognitive systems that closely simulate human-like functions within computers. By adopting this approach, complex medical problems can be addressed with improved accuracy and expedience. The results demonstrate the system's capability to deliver reliable diagnoses and corresponding treatment recommendations. Overall, this research showcases how cutting-edge technological solutions can revolutionize medical practices, paving the way for more effective patient care and management.