Medicine
Showing 11-17 of 17 Results
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Behzad Naderalvojoud
Biostatistician 2, Computational Medicine
BioBehzad Naderalvojoud is a biomedical informatics scientist at the Stanford Center for Biomedical Informatics Research. He received his Ph.D. degree in computer science at Hacettepe University, Turkey, in 2020. He is immersed in the fields of machine learning, deep learning, natural language understanding, and Big data analytics and works on health knowledge discovery platforms that transfer Big health data from volume-based to value-based by generating relational knowledge leading to innovative treatments, predictive therapeutic outcomes, and early diagnosis. He was the leader of many industrial AI projects in the fields of healthcare intelligence and information management in the Eureka cluster programs.
Dr. Naderalvojoud has published several papers in the field of natural language understanding by working on word sense disambiguation, sentiment analysis, neural word embeddings, and deep learning models through national and international projects.
He is currently working on the funded NLM grant project "Advancing Knowledge Discovery for Postoperative Pain Management" under the supervision of Dr. Tina Hernandez-Boussard. He develops descriptive, predictive, and analytical tools using OMOP CDM for postoperative pain research to facilitate timely generation of evidence across multiple populations and settings. -
Martin O'Connor
Software Dvlpr 3, Computational Medicine
Current Role at StanfordResearch software developer at Stanford Center for Biomedical Informatics Research (BMIR)
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Walter Sujansky
Adjunct Professor, Division of Computational Medicine
BioWalter Sujansky, MD PhD is an Adjunct Professor of Biomedical Informatics at the Stanford Center for Biomedical Informatics Research in the Stanford Department of Medicine. Dr. Sujansky co-teaches BMI-210 Modeling Biomedical Systems, where he lectures on a variety of topics, including deep neural networks, probabilistic reasoning, electronic health records, and health data integration and interoperability. He also advises students in the Biomedical Data Science Graduate Program, an interdisciplinary graduate and postdoctoral training program that is part of the Department of Biomedical Data Science. His research interests include the modeling of biomedical concepts based on formal logic and the engineering of features for biomedical machine learning algorithms.
Dr. Sujansky earned an M.D. and a Ph.D. in Medical Informatics from Stanford University, where his doctoral research addressed heterogeneous database integration and clinical decision support. He also earned a B.A. in Economics from Harvard University.
Dr. Sujansky is also the managing consultant at Sujansky & Associates, LLC, a consulting firm that specializes in the representation, management, and analysis of clinical data in information systems. In this capacity, his work focuses on the modeling of complex biomedical data related to patient phenotyping, clinical genomics, quality measurement, automated decision support, and machine learning. His firm has helped to develop shared computing resources such as the California Joint Replacement Registry and the Laboratory Interoperability Data Repository. The firm's clients include the federal and state governments, non-profit organizations, health information system developers, and drug/device manufacturers. Dr. Sujansky also provides forensic analysis of health information technologies for medical malpractice and intellectual property litigation.
