Journal Clubs

Dr. Mackenzie Meni, Ph.D. delved into the recently published work, “Unified Clinical Vocabulary Embeddings for Advancing Precision Medicine” in our latest Journal Club. She explained how the study proposes a solution by unifying seven medical vocabularies and validating clinical vocabulary embeddings using real-world data from 4.57 million patients. This innovative approach bridges gaps in training datasets, reduces bias, and supports the development of AI models that better represent clinical relationships for population-level and patient-specific healthcare applications.

Prompt engineering has emerged as a powerful technique to enhance model performance without altering core parameters, yet there remains a lack of systematic understanding of its diverse methods and applications. Dr. Hu delved into the recently published work “A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications” presenting insights from a comprehensive survey on prompt engineering. He discussed the taxonomy of prompting techniques, their applications across AI tasks, and the strengths and limitations of different approaches. By organizing this rapidly evolving field, the research provides a roadmap for future advancements in optimizing AI for real-world applications.