CPR Seminar - Zhiyong Lu
Transforming Medicine with AI: from PubMed Search to Machine Diagnosis
The explosion of biomedical big data and information in the past decade or so has created new opportunities for discoveries to improve the treatment and prevention of human diseases. But the large body of knowledge—mostly exists as free text in journal articles for humans to read—presents a grand new challenge: individual scientists around the world are increasingly finding themselves overwhelmed by the sheer volume of research literature and are struggling to keep up to date and to make sense of this wealth of textual information. Our research aims to break down this barrier and to empower scientists towards accelerated knowledge discovery. In this talk, I will present our work on developing large-scale, machine-learning based tools for better understanding scientific text in the biomedical literature. Moreover, I will demonstrate their uses in some real-world applications such as improving PubMed searches, scaling up data curation with PubTator, and taming COVID-19 pandemic paper tsunami in LitCovid.
Dr. Zhiyong Lu is a Senior Investigator at the National Library of Medicine’s (NLM) Intramural Research Program, leading research in biomedical text and image processing, information retrieval, and AI/machine learning. In his role as Deputy Director for Literature Search at National Center of Biotechnology Information (NCBI), Dr. Lu directs the overall R&D efforts to improve literature search and information access in resources like PubMed and LitCovid, which are used by millions worldwide each day. With over 300 peer-reviewed publications, Dr. Lu is a highly cited author and a Fellow of the American College of Medical Informatics (ACMI). Additionally, Dr. Lu serves as an Associate Editor of Bioinformatics, and Organizer of the BioCreative challenge. Dr. Lu has also mentored over 50 trainees throughout his career, many of whom have gone on to become independent faculty members/researchers at academic institutions in the US, Europe, and Asia.