Topics:
Discussions will address the potential of Al to transform patient care, medical research, and clinical decision-making, examining how foundation models and large language models can enhance health-related content generation, patient interaction, and clinical documentation. Advancements in self- supervised learning and continuous training will be covered, along with Al's applications in diagnostics, treatment, and evidence-based medicine, where retrieval-augmented generation (RAG) can improve accuracy and reliability in medical content.
On the challenges side, the Summit will confront issues like source attribution, Al bias, trust, and hallucinations, along with disparities in access and translational gaps between research and clinical practice. Ethical considerations will be central, as will the need for high-quality, diverse data, and secure cloud computation. Regulatory compliance and seamless integration into healthcare workflows will be discussed, emphasizing training and user experience to foster adoption and trust.
