Artificial General Intelligence (AGI) in Healthcare

The course "Artificial General Intelligence (AGI) in Healthcare" offers a comprehensive exploration into the evolving role of human-level artificial intelligence within the medical and healthcare ecosystem. Beginning with foundational concepts, students will first learn the critical distinctions between AGI and narrow AI, and the defining characteristics of AGI such as reasoning, transfer learning, and autonomy. The course then discusses why AGI is essential to healthcare, setting the stage with a global view of the current state of AGI research. Students will trace technological milestones from expert systems to deep learning and AGI, gaining historical context supported by real-world case studies like IBM Watson, DeepMind’s AlphaFold, and GPT’s role in clinical research. A detailed analysis of AI’s current limitations in healthcare further clarifies why AGI represents the next frontier.Diving deeper, learners will study leading cognitive architectures such as ACT-R, Soar, OpenCog, and Sigma, and examine cognitive processes like memory, attention, and consciousness within AGI systems. The course contrasts brain-inspired models and symbolic approaches and shows how AGI enables multi-modal data interpretation across text, imaging, voice, and sensors. Students will understand contextual patient history integration, adaptive decision-making across disciplines, and review a hypothetical case study of AGI diagnosing rare diseases. Core clinical applications include interpreting genomic data for customized treatment, predictive disease modeling, and drug matching with side-effect mitigation.In surgery, students will explore human-AI collaboration, fully autonomous robotic surge