Michael Hogarth

4.5k citations
58 papers · 1.7k indexed · 1 hit paper · h-index 15

Impact in

Papers in

Michael Hogarth

52 papers receiving 1.7k citations

Hit Papers

Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum 2023 · 1.2k citations
1.2k20232026202420252505007501000

Peers

Michael Hogarth
Comparison fields: 5 of 139
  • Health Informatics 879
  • Family Practice 155
  • Health Information Management 142
  • Artificial Intelligence 550
  • Radiology, Nuclear Medicine and Imaging 387
Replace Adam Poliak with:
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Michael Hogarth relative to Adam Poliak United States Adam Poliak's profile →
Citations per field
00.5×2.7×
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Citations per year

Countries citing papers authored by Michael Hogarth

Since Specialization
Citations

This map shows the geographic impact of Michael Hogarth'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 Michael Hogarth with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Hogarth more than expected).

Fields of papers citing papers by Michael Hogarth

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Hogarth. 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 Michael Hogarth. The network helps show where Michael Hogarth may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Michael Hogarth, 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 Michael Hogarth Line = papers co-authored together Michael Hogarth links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20248
3 202416
4 20241
5 20242
6 20243
7
Comparing Physician and Artificial Intelligence Chatbot Responses to Patient Questions Posted to a Public Social Media Forum
Hit paper breakdown →
20231184
8 20230
9 20233
10 20235
11 20230
12 20236
13 20224
14 202115
15 20204
16 202032
17 201333
18
jTerm: an open source terminology server.
20031
19 200223
20
jTerm: A Server for Terminological Systems
20011

About Michael Hogarth

Michael Hogarth is a scholar working on Medical Terminology, Health Informatics, Health Information Management, Family Practice and Artificial Intelligence, having authored 58 papers that have together received 1.7k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (12 papers), Electronic Health Records Systems (10 papers), Semantic Web and Ontologies (5 papers), Healthcare Systems and Technology (4 papers), Machine Learning in Healthcare (4 papers), Ethics in Clinical Research (4 papers), Artificial Intelligence in Healthcare and Education (4 papers) and Radiology practices and education (4 papers). The work is most often cited by research in Health Informatics (879 citations), Family Practice (155 citations), Health Information Management (142 citations), Artificial Intelligence (550 citations) and Radiology, Nuclear Medicine and Imaging (387 citations). Michael Hogarth has collaborated with scholars based in United States, Saudi Arabia and Germany. Frequent co-authors include John W. Ayers, Davey M. Smith, Mark Dredze, Eric C. Leas, Chris Longhurst, Adam Poliak, Aaron M. Goodman, Dennis J. Faix, Thomas F. Anders and Lydia Pleotis Howell. Their work appears in journals such as Journal of Medical Internet Research, Academic Medicine, JAMA Internal Medicine, Learning Health Systems and Neuroinformatics.

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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