AMIA Edward H. Shortliffe Doctoral Dissertation Award Presentations
Presentation Time: 01:45 PM - 03:15 PM
The American Medical Informatics Association (AMIA) proudly announces the recipients of the 2024 Edward H. Shortliffe Doctoral Dissertation Award. Dr. Alice Tang of the University of California, San Francisco, earned the First Prize for her dissertation titled "Leveraging Clinical Data and Knowledge Networks to Derive Insights Into Alzheimer's Disease." Dr. Linying Zhang of Columbia University received an Honorable Mention for her dissertation "Causal Machine Learning for Reliable Real-World Evidence Generation in Healthcare." Both dissertations represent exceptional contributions to the field of biomedical informatics and demonstrate the innovative application of informatics in healthcare research.
Join us at the AMIA 2024 Annual Symposium, November 9-13 in San Francisco, where Drs. Tang and Zhang will present their groundbreaking work during scientific session S38. Dr. Tang’s research focuses on identifying patients at high risk of dementia using clinical data, with broad implications for precision medicine. Dr. Zhang’s work integrates machine learning and informatics methodologies to advance reliable evidence generation from complex real-world healthcare data.
CME Learning Objectives:
1. Evaluate cutting-edge informatics research methodologies that enhance clinical data analysis and contribute to evidence-based healthcare practices.
2. Recognize the impact of informatics research in advancing precision medicine and real-world data applications for improved patient care
Speaker(s):
Alice Tang, PhD
UCSF
Linying Zhang, PhD
Washington University in St. Louis
Presentation Time: 01:45 PM - 03:15 PM
The American Medical Informatics Association (AMIA) proudly announces the recipients of the 2024 Edward H. Shortliffe Doctoral Dissertation Award. Dr. Alice Tang of the University of California, San Francisco, earned the First Prize for her dissertation titled "Leveraging Clinical Data and Knowledge Networks to Derive Insights Into Alzheimer's Disease." Dr. Linying Zhang of Columbia University received an Honorable Mention for her dissertation "Causal Machine Learning for Reliable Real-World Evidence Generation in Healthcare." Both dissertations represent exceptional contributions to the field of biomedical informatics and demonstrate the innovative application of informatics in healthcare research.
Join us at the AMIA 2024 Annual Symposium, November 9-13 in San Francisco, where Drs. Tang and Zhang will present their groundbreaking work during scientific session S38. Dr. Tang’s research focuses on identifying patients at high risk of dementia using clinical data, with broad implications for precision medicine. Dr. Zhang’s work integrates machine learning and informatics methodologies to advance reliable evidence generation from complex real-world healthcare data.
CME Learning Objectives:
1. Evaluate cutting-edge informatics research methodologies that enhance clinical data analysis and contribute to evidence-based healthcare practices.
2. Recognize the impact of informatics research in advancing precision medicine and real-world data applications for improved patient care
Speaker(s):
Alice Tang, PhD
UCSF
Linying Zhang, PhD
Washington University in St. Louis
AMIA Edward H. Shortliffe Doctoral Dissertation Award Presentations
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