Travis R. Goodwin

743 citations
42 papers · 428 indexed · h-index 12

Travis R. Goodwin

42 papers receiving 408 citations

Peers

Travis R. Goodwin
Comparison fields: 5 of 89
  • Health Informatics 26
  • Artificial Intelligence 281
  • Health Information Management 40
  • Issues, ethics and legal aspects 7
  • Management Science and Operations Research 57
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Oladimeji Farri United States
Giorgio Leonardi Italy
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Citations per year

Countries citing papers authored by Travis R. Goodwin

Since Specialization
Citations

This map shows the geographic impact of Travis R. Goodwin's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Travis R. Goodwin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Travis R. Goodwin more than expected).

Fields of papers citing papers by Travis R. Goodwin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Travis R. Goodwin. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Travis R. Goodwin. The network helps show where Travis R. Goodwin may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Travis R. Goodwin, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Travis R. Goodwin Line = papers co-authored together Travis R. Goodwin links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20222
2 202265
3 202015
4
NLM at TREC 2020 Health Misinformation and Deep Learning Tracks.
20201
5 20205
6 202023
7
Overview of the TAC 2019 Track on Drug-Drug Interaction Extraction from Drug Labels.
20192
8 201921
9
Overview of the TAC 2018 Drug-Drug Interaction Extraction from Drug Labels Track.
20188
10
UTD HLTRI at TREC 2017: Precision Medicine Track.
20177
11 201711
12 20176
13
Active Deep Learning-Based Annotation of Electroencephalography Reports for Cohort Identification.
20178
14
Deep Learning from EEG Reports for Inferring Underspecified Information.
20176
15 201647
16
UTD at TREC 2014: Query Expansion for Clinical Decision Support
201417
17
UTDHLT: COPACETIC System for Choosing Plausible Alternatives
201211
18 19681
19 19661
20 19567

About Travis R. Goodwin

Travis R. Goodwin is a scholar working on Health Information Management, Artificial Intelligence and Issues, ethics and legal aspects, having authored 42 papers that have together received 428 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (22 papers), Topic Modeling (18 papers), Machine Learning in Healthcare (11 papers), Natural Language Processing Techniques (10 papers), Advanced Text Analysis Techniques (5 papers), Semantic Web and Ontologies (5 papers), Electronic Health Records Systems (4 papers) and Genomics and Rare Diseases (2 papers). The work is most often cited by research in Health Informatics (26 citations), Artificial Intelligence (281 citations) and Health Information Management (40 citations). Travis R. Goodwin has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Sanda M. Harabagiu, Dina Demner‐Fushman, Chun‐Hung Chen, Nurçin Çelik, Jie Xu, Michael A. Skinner, Kirk Roberts, Bryan Rink, Yassine Mrabet and Asma Ben Abacha. Their work appears in journals such as Journal of the American Medical Informatics Association, Scientific Data and Journal of Biomedical Informatics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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