Artificial Intelligence and Machine Learning in Pediatric Biomedical Research
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Amazon Web Services782 тыс
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02.08.19 – 1 14010:30Популярные
32 дня – 4197:08
45 дней – 6614:51Опубликовано 2 августа 2019, 17:06
Prof. Judith Dexheimer, Associate Professor at Cincinnati Children's Hospital Medical Center
Dr. Dexheimer is an Associate Professor of Pediatrics at Cincinnati Children’s Hospital Medical Center and the University of Cincinnati. She is a clinical informaticist working on the development and implementation of machine learning applications into clinical care. Her research focus areas include machine learning techniques, real-time patient identification system, disparate data merging, and applications of clinical data. Dr. Dexheimer co-leads the Decision Support Analytics Workgroup (DSAW), which investigates the links between the effectiveness of clinical decision support (CDS), patient safety, and user efficiency. This research has demonstrated ties between decreasing alert burden on clinicians, increasing CDS alert salience, and improving patient outcomes.
She will discuss the role and impact of artificial intelligence and machine learning in research with the electronic health record, explore unique aspects of conducting work in pediatrics with biomedical informatics, and examine what is being done now with machine learning and what the future might hold.
Dr. Dexheimer is an Associate Professor of Pediatrics at Cincinnati Children’s Hospital Medical Center and the University of Cincinnati. She is a clinical informaticist working on the development and implementation of machine learning applications into clinical care. Her research focus areas include machine learning techniques, real-time patient identification system, disparate data merging, and applications of clinical data. Dr. Dexheimer co-leads the Decision Support Analytics Workgroup (DSAW), which investigates the links between the effectiveness of clinical decision support (CDS), patient safety, and user efficiency. This research has demonstrated ties between decreasing alert burden on clinicians, increasing CDS alert salience, and improving patient outcomes.
She will discuss the role and impact of artificial intelligence and machine learning in research with the electronic health record, explore unique aspects of conducting work in pediatrics with biomedical informatics, and examine what is being done now with machine learning and what the future might hold.
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