UCSF and UC Berkeley's Computational Precision Health
Dr. Ahmed Alaa is an Assistant Professor of Computational Precision Health at the University of California, Berkeley and the University of California, San Francisco. His research focuses on developing machine learning (ML) methods to solve real-world problems in precision medicine. The overarching goal of his research is to develop ML models that can identify the best treatment for each individual patient based on their clinical features and characteristics. To this end, his lab focuses on developing multimodal deep learning models to learn representations of patient data across different...
Epidemiology & Biostatistics - UCSF School of Medicine
Efstathios (Stathis) D. Gennatas, MBBS AICSM PhD, is an Assistant Professor in the Department of Epidemiology and Biostatistics at UCSF. His work includes applied data science in basic research, clinical predictive modeling using electronic health records to improve patient outcomes, and the development of machine learning methods and software for biomedical data analysis. His overarching goal is to help make precision medicine a reality in a safe, fair, and efficient way. He is an affiliate of the Institute for Global Health Sciences, the Bakar Computational Health Sciences...
University of California San Francisco, Department of Anesthesia and Perioperative Care
Dr Pirracchio is a M.D., MPH, Ph.D., hailing from Paris. He obtained his M.D. in 2003, with a specialization in Anesthesiology and Critical Care Medicine. In 2008, he obtained an MPH and completed his doctoral studies in Biostatistics in Paris, France in 2012. In 2012-2013, he spent a year as a postdoctoral fellow in Biostatistics in the School of Public Health at the University of California, Berkeley. Back in Paris, he was the clinical director of the surgical and trauma ICU at European Hospital Georges Pompidou (2013-2015) and a researcher in Biostatistics with the INSERM U-1153...
UCSF Department of Radiation Oncology - UCSF Department of Epidemiology and Biostatistics
Following his doctoral training in Medical Physics at UCLA and a subsequent fellowship and clinical residency in Therapeutic Medical Physics at the University of Pennsylvania, he embarked on a journey to explore and develop machine learning algorithms and advanced models for their application in medicine. These were constructed with the aim to predict patient outcomes and tailor treatments according to the type and quality of data available, with a particular focus on prostate and thoracic cancer patients. In addition to these interests, his professional journey has led me to develop...