AI in health care threat detection

Abstract

Medical detection and management through Artificial Intelligence (AI) constitutes a transformative healthcare force which identifies and handles health threats including infectious diseases combined with chronic conditions and new worldwide health challenges. Worldwide healthcare systems reveal extensive problems that the fast-evolving AI technologies encompassing ML, DL and NLP demonstrate ability to resolve. AI stands as a promising solution to minimize both health threats' mortality rates and morbidity through diagnostic process automation as well as surveillance capabilities improvement and enhanced decision support systems. The journal evaluates how AI detects health threats through its analysis of large datasets while identifying discreet patterns to create predictive models that help with early detections. We review the multiple obstacles encountered during traditional health threat detection through complex datasets combined with human resource restrictions and diagnosis scheduling problems. At the same time, we demonstrate how AI-based systems have produced effective solutions. The review presents actual projects where AI technology enhances healthcare by detecting cancer and forecasting disease spread along with monitoring antimicrobial resistance and mental health evaluation. The journal analyzes both ethical dilemmas and privacy issues tangled with AI implementation together with its integration capability in current healthcare infrastructure. The journal highlights how AI has substantial power to transform healthcare threat detection and requires proper execution and continuous oversight and interdisciplinary team effort to optimize performance while handling risks effectively.

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