Cognitive Computing in Healthcare: Past Lessons, Present Realities, and Future Horizons

Abstract

The healthcare sector experiences transformation through cognitive computing which provides improved diagnosis methods and designs treatment plans as well as cares for patients and operates medical facilities. Modern medical decision-making has experienced a revolution through both early expert systems and current AI-driven diagnostics together with robotic surgery and precise medical treatments. The vast potential requires solution of privacy issues with datasets together with algorithmic discrimination prevention and adaptation of relevant regulations and resolution of ethical problems. AI healthcare development will focus on three main areas which involve predictive knowledge analysis and real-time illness prevention along with sophisticated drug innovation processes to deliver patient-specific proactive medical services in the future. The introduction of AI must meet both ethical requirements and legal responsibilities in order to gain public acceptance because patient rights and AI clarity and cybersecurity protection matter most. A complete adoption of cognitive computing requires global collaboration between healthcare professionals and strong regulatory frameworks as well as AI literacy for medical staff and cognitive computing implementation methods. A responsible implementation of AI healthcare will generate an enhanced system that provides more precise and efficient patient-focused medical treatment to enhance global health results.