Jeremy Petch

25 papers receiving 750 citations

Jeremy Petch's Hit Papers

Opening the Black Box: The Promise and Limitations of Explainable Machine Learning in Cardiology 2021 · 335 citations
3350+1+3Years since publication100200300

Peers

Jeremy Petch
Comparison fields: 5 of 131
  • Health Informatics 60
  • Health Information Management 37
  • General Health Professions 109
  • Applied Psychology 19
  • Artificial Intelligence 117
Replace Getu Gamo Sagaro with:
Getu Gamo Sagaro Italy
Tsair‐Wei Chien Taiwan
Bilal A. Mateen United Kingdom
Santiago Romero‐Brufau United States
Tammy Jiang United States
Anthony Solomonides United States
Jiancheng Ye United States
Sanjeev P. Bhavnani United States
Johan Gustav Bellika Norway
Kwang‐Sig Lee South Korea
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Citations per year

Countries citing papers authored by Jeremy Petch

Since Specialization
Citations

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

Fields of papers citing papers by Jeremy Petch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Opening the Black Box: The Promise and Limitations of Explainable Machine Learning in Cardiology
Hit paper breakdown →
2021335
2 2015151
3 202080
4 202247
5 202319
6 201316
7 202415
8 202313
9 201211
10 202310
11 202110
12 20239
13 20197
14 20227
15 20226
16 20236
17 20176
18 20233
19 20252
20 20222

About Jeremy Petch

Jeremy Petch is a scholar working on General Health Professions, Pediatrics, Perinatology and Child Health, Public Health, Environmental and Occupational Health, Radiology, Nuclear Medicine and Imaging and Economics and Econometrics, having authored 29 papers that have together received 760 indexed citations. Recurring topics across this work include Ethics and Legal Issues in Pediatric Healthcare (3 papers), Palliative Care and End-of-Life Issues (3 papers), Digital Mental Health Interventions (2 papers), Healthcare Policy and Management (2 papers), Childhood Cancer Survivors' Quality of Life (2 papers), Statistical Methods in Clinical Trials (2 papers), Artificial Intelligence in Healthcare and Education (2 papers) and Genetic Associations and Epidemiology (2 papers). The work is most often cited by research in Health Informatics (60 citations), Health Information Management (37 citations), General Health Professions (109 citations), Applied Psychology (19 citations) and Artificial Intelligence (117 citations). Jeremy Petch has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include Shuang Di, Laura C. Rosella, Walter P. Wodchis, Andrew D. Pinto, Heather Manson, Vivek Goel, Andrew Calzavara, P.J. Devereaux, Walter Nelson and Michael McGillion. Their work appears in journals such as Journal of Medical Internet Research, Health Policy, Nature Communications, Clinical Cancer Research and Scientific Reports.

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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