Скачать с ютуб A Real Discussion about Artificial Intelligence (AI) in Research в хорошем качестве

A Real Discussion about Artificial Intelligence (AI) in Research

A Real Discussion about Artificial Intelligence (AI) in Research. Follow the UCSF Division of Prevention Science on Social: ☀️UCSF Prevention Science Linkedin   / ucsf-dps   ☀️UCSF Prevention Science on YouTube    / @ucsfcenterforaidspreventio3461   ☀️Sign up for our quarterly CAPS/PRC e-newsletter - https://lnkd.in/gCzkZQE Dr. William Brown, III is an Associate Professor of Medicine & Epidemiology and Biostatistics at UC San Francisco, an AMIA Board Director and was a Vice Chair for the AMIA 2022 conference, and a John A. Watson Faculty Scholar. He is the Founding Director of CODE Lab, Director of DEI for the Bakar Computational Health Science Institute, Co-Director of the T32 DaTABASE for Health Disparities Research Fellowship, Associate Director at the Research Coordinating Center to Reduce Disparities in Multiple Chronic Diseases (RCC RD-MCD), and Implementation Science Lead for the Center for Digital Health Innovation. His research involves Big Data, mHealth, Natural Language Processing, Machine Learning, and Standards [FHIR, OMOP, UMLS, etc.] as applied to clinical and behavioral health disparities research, with underserved communities. Using community-based participatory research he works to reduce chronic illness (HIV, diabetes, opioids) and health disparities among vulnerable populations (i.e., African-Americans, Latinos, youth, and LGBT). He also teaches and mentors graduate students. Session Moderator: Tor Neilands, PhD, CAPS Professor of Medicine and Director of the CAPS Methods Core ImageTorsten Neilands, Ph.D., Professor of Medicine at UCSF, trained as a social psychologist and spent eight years as a statistical consultant at an academic computing center before coming to CAPS in 2001. His methodological areas of interest are multivariate statistical models with a special interest in latent variable models for survey scale development and validation, and mixed effects models for clustered and longitudinal data, including dyadic data. He is the PI of an NIH-sponsored R25 research education grant to foster grant-writing and related research capacity-building for early-career faculty working in U.S. minority communities to prevent the spread of HIV/AIDS and STIs and to improve the lives of those living with HIV/AIDS. He also actively collaborates as a senior statistician and quantitative methods co-investigator on multiple HIV prevention and tobacco prevention research projects. Dr. Neilands is the Director of the CAPS Methods Core. A CAPS Methods Core Town Hall. Recorded Tuesday, February. 13th, 2024. 0:00 Introductions 1:44 AI General Overview 3:27 AI as a Tool 4:48 What is AI? 8:32 AI in Research 16:20 Disadvantages and Challenges 22:42 How to Use AI in Research 26:44 Open-Source Platforms 28:46 Using AI in Research Writing 39:36 Conclusion 40:27 ai.ucsf.edu 41:01 Bias in AI 48:33 Discussion and Q & A