A Perspective on AI for Healthcare

This presentation provides a comprehensive perspective on the use of Artificial Intelligence in healthcare. It begins by exploring the philosophical and historical roots of AI, tracing concepts from Aristotle's laws of association to the dawn of connectionism, which views intelligence as emerging from interconnected networks, much like the human brain. The talk then outlines the key breakthroughs that enabled modern AI—namely, the explosion of data, increased computational power, and advanced algorithms. A core focus is on the unique nature of healthcare data, which is often multimodal, high-dimensional, sensitive, and heterogeneous, presenting both challenges and opportunities. The presentation then details a wide range of AI applications in health, including disease diagnosis, personalized treatment, robotic surgery, clinical trial research, and automating repetitive tasks like analyzing medical images. A significant portion is dedicated to AI's transformative role in drug discovery, where it accelerates target identification, virtual screening, and biomarker discovery. Finally, the presentation uses the global challenge of Antimicrobial Resistance (AMR) as a powerful case study, illustrating how AI is being deployed to discover new antibiotics, predict resistance, optimize treatments, and conduct global surveillance, while also acknowledging the ongoing challenges of data quality, model interpretability, and integration into existing healthcare systems.