denotes an abstract that is clinically relevant.
denotes that this is a ticketed session.
Hematology Disease Topics & Pathways:
artificial intelligence (AI), Technology and Procedures, machine learning
Dr. Nazha will discuss the basics and the differences between AI, ML, and deep learning (DL). He will review the forces that drive the excitement about AI in healthcare and why AI could be valuable in advancing research in the medical field. He will also dive deep into the mechanics of how ML and DL algorithms work and the optimal ways to use them in medicine. Finally, Dr. Nazha will discuss some of the use cases and novel advances in ML and DL in real life and medicine.
Dr. Olivier Elemento will discuss some of the recent applications of ML in diagnostic hematology. He will address the strengths and weaknesses of these methods including accuracy and biases, the extent of their current clinical use, and potential barriers to broader implementation and clinical application. Dr. Elemento will also outline future potential applications based on recent developments in the field of ML and newly available datasets.
Dr. Ilana Goldberg will discuss the current trends to incorporate AI and ML into healthcare diagnostics and treatments. She will discuss how these technology tools are being introduced in the field of hematology and possibilities for how they can continue to be developed for blood diseases.
Dr. Shannon McWeeney will review the process of transitioning ML algorithms and models from research to the clinic which include validation, bias assessment, hardening, and deployment. She will highlight current challenges in clinical data in the EHR for both model development and deployment. Dr. McWeeney will also discuss the governance, regulatory, and oversight considerations for AI/ML-based software at institutional and federal levels. Lastly, she will examine what is needed to ensure actionable decision support regarding transparency and explaining these technologies.