Correction to: The role of machine learning in clinical research: transforming the future of evidence generation.
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2021-09
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Abstract
Following the publication of the original article [1], we were notified that current affiliations 17, 18 and 19 were erroneously added to the first author rather than the senior author (Marzyeh Ghassemi). The original article has now been corrected.
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Weissler, E Hope, Tristan Naumann, Tomas Andersson, Rajesh Ranganath, Olivier Elemento, Yuan Luo, Daniel F Freitag, James Benoit, et al. (2021). Correction to: The role of machine learning in clinical research: transforming the future of evidence generation. Trials, 22(1). p. 593. 10.1186/s13063-021-05571-4 Retrieved from https://hdl.handle.net/10161/30730.
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Scholars@Duke
E. Hope Weissler
Scott Haden Kollins
Scott H. Kollins, PhD received his undergraduate degree in psychology from Duke and his Master’s and Doctorate degrees in Clinical Psychology from Auburn University. After completing his clinical internship at the University of Mississippi Medical Center, where he served as Chief Intern, he joined the faculty of the Department of Psychology at Western Michigan University for three years, before joining the Duke faculty in 2000. Dr. Kollins has published more than 125 scientific papers in peer-reviewed journals. Over the past 10 years, his research has been supported by 6 different federal agencies, including NICHD, NIDA, NIMH, NIEHS, NINDS, and EPA, and he currently holds a mid-career K24 award from NIDA. He has also served as PI on more than 40 industry-funded clinical trials and is a consultant to a number of pharmaceutical companies in the area of ADHD clinical psychopharmacology. He has served as a standing member of the Child Psychopathology and Developmental Disabilities study section and also served as an ad-hoc reviewer for 10 additional NIH study sections and 7 international granting agencies. He is an Associate Editor for the Journal of Attention Disorders and has reviewed for more than 50 different peer-reviewed journals. He is an elected member of the College on Problems of Drug Dependence and the American College of Neuropsychopharmacology. Dr. Kollins is a licensed clinical psychologist and maintains a practice through the ADHD Program’s outpatient clinic. His research interests are in the areas of psychopharmacology and the intersection of ADHD and substance abuse, particularly cigarette smoking.
Erich Senin Huang
Former Chief Data Officer for Quality, Duke Health
Former Director of Duke Forge
Former Director of Duke Crucible
Former Assistant Dean for Biomedical Informatics
Dr. Huang is currently Chief Science & Innovation Officer for Onduo by Verily, and Head of Clinical Informatics at Verily (Google's life sciences subsidiary), and is now adjunct faculty at Duke. Dr. Huang’s research interests span applied machine learning, research provenance and data infrastructure. Projects include building data provenance tools funded by the NIH’s Big Data to Knowledge program, regulatory science funded by the Burroughs Wellcome Foundation. Applied machine learning applications include “Deep Care Management” a highly interdisciplinary project with Duke Connected Care, Duke’s Accountable Care Organization, that integrates claims and EHR data for predicting unplanned admissions and risk stratifying patients for case management; CALYPSO, a collaboration with the Department of Surgery for utilizing machine learning to predict surgical complications. My team is also building the data platform for the Department of Surgery's "1000 Patients Project" an intensive biospecimen and biomarker study based around patients undergoing the controlled injury of surgery.
As Director of Duke Forge, Dr. Huang is working to build a data science culture and infrastructure across Duke University that focuses on actionable health data science. The Forge emphasizes scientific rigor, awareness that technology does not supersede clinicians’ responsibilities and human relationship with their patients, and the role of data science in society.
Unless otherwise indicated, scholarly articles published by Duke faculty members are made available here with a CC-BY-NC (Creative Commons Attribution Non-Commercial) license, as enabled by the Duke Open Access Policy. If you wish to use the materials in ways not already permitted under CC-BY-NC, please consult the copyright owner. Other materials are made available here through the author’s grant of a non-exclusive license to make their work openly accessible.