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Travis
Goodwin
,
PhD
Postdoctoral Research Fellow
Location: 
38A
/
10N1003M
Phone Number: (
301
827-6109
Expertise and Research Interests: 

Travis R. Goodwin, PhD, joined the Communications Engineering Branch at the Lister Hill National Center for Biomedical Communications (LHNCBC) as a Postdoctoral Research Fellow in June 2018. Dr. Goodwin completed his PhD in Computer Science at the University of Texas at Dallas (UTD) in May 2018. His PhD research focused on Bayesian and (deep) neural methods for medical question answering, clinical decision support, and medical information retrieval. He is currently working on applying deep learning techniques for predictive modeling and laboratory test ordering under the mentorship of Dr. Dina Demner-Fushman.

Professional Activities: 

Dr. Goodwin joined the Student Editorial Board (SEB) of the Journal of the American Medical Informatics Association (JAMIA) in 2018, and is a member of the American Medical Informatics Association (AMIA), the Association for Computational Linguistics (ACL), and the Association for Computing Machinery’s (ACM) Special Interest Group on Information Retrieval (SIGIR).

Honors and Awards: 

Dr. Goodwin was selected into the NIH Independent Research Scholar Program in 2019. Dr. Goodwin’s work on early prediction of hospital acquired pneumonia won a Fellows Award for Research Excellence (FARE) award in the 2020 competition. His doctoral dissertation entitled “Medical Question Answering and Patient Cohort Retrieval” won first prize in the 2019 AMIA Doctoral Dissertation Awards.

Publications/Tools by Travis Goodwin: 
Goodwin T, Demner-Fushman D. A customizable deep learning model for nosocomial risk prediction from critical care notes with indirect supervision. Journal of the American Medical Informatics Association, 2020: 27 (4), 567-576.
Goodwin T, Demner-Fushman D. Deep Learning from Incomplete Data: Detecting Imminent Risk of Hospital-acquired Pneumonia in ICU Patients. Proceedings of the AMIA 2019 Annual Symposium, Washington, DC, USA, November 17-20, 2019.
Goodwin T, Demner-Fushman D, Fung K, Do P. Overview of the TAC 2019 Track on Drug-Drug Interaction Extraction from Drug Label. Proceedings of the Text Analysis Conference (TAC) 20 19, Gathersburg, MD, USA, November 12-13, 2019.
Goodwin T, Demner-Fushman D. Bridging the Knowledge Gap: Enhancing Question Answering with World and Domain Knowledge. arXiv preprint arXiv:1910.07429
Ben Abacha A, Mrabet Y, Sharp M, Goodwin T, Shooshan S, Demner-Fushman D. Bridging the Gap Between Consumers’ Medication Questions and Trusted Answers. Stud Health Technol Inform. 2019 Aug 21;264:25-29. doi: 10.3233/SHTI190176.
Ben Abacha A, Mrabet Y, Sharp M, Goodwin T, Shooshan S, Demner-Fushman D. Bridging the Gap Between Consumers' Medication Questions and Trusted Answers. Studies in health technology and informatics, 264, pp.25-29, 2019.
Goodwin T, Harabagiu S. The Impact of Inferring Treatments on Information Retrieval for Precision Medicine. Proceedings of the AMIA 2019 Informatics Summit, San Francisco, CA, USA, March 25-28, 2019.
Demner-Fushman D, Fung K, Do P, Boyce R, Goodwin T. Overview of the TAC 2018 Drug-Drug Interaction Extraction from Drug Labels Track. Proceedings of the Text Analysis Conference (TAC) 2018, Gaithersburg, MD, USA, November 13-14, 2018.