Tom Pollard

39 papers receiving 1.8k citations

Tom Pollard's Hit Papers

Automated real-world data integration improves cancer outcome prediction 2024 · 92 citations
920+3+6Years since publication100200300400

Peers

Tom Pollard
Comparison fields: 5 of 132
  • Health Informatics 190
  • Critical Care and Intensive Care Medicine 160
  • Health Information Management 134
  • Emergency Medicine 152
  • Pulmonary and Respiratory Medicine 406
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Erica Maffei Italy
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Citations per year

Countries citing papers authored by Tom Pollard

Since Specialization
Citations

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

Fields of papers citing papers by Tom Pollard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Mechanical power of ventilation is associated with mortality in critically ill patients: an analysis of patients in two observational cohorts
Hit paper breakdown →
2018422
2
The MIMIC Code Repository: enabling reproducibility in critical care research
Hit paper breakdown →
2017300
3 2015170
4 2018137
5
Automated real-world data integration improves cancer outcome prediction
Hit paper breakdown →
202492
6 201584
7 202483
8 201481
9
Reproducibility in critical care: a mortality prediction case study
201763
10 201662
11 201936
12 202034
13 201631
14 201829
15
Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference
201426
16 201723
17 202122
18 202219
19 201916
20 202115

About Tom Pollard

Tom Pollard is a scholar working on Health Informatics, Health Information Management, Information Systems and Management, Artificial Intelligence and Public Health, Environmental and Occupational Health, having authored 44 papers that have together received 1.9k indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (11 papers), Artificial Intelligence in Healthcare (7 papers), Machine Learning in Healthcare (7 papers), Ethics in Clinical Research (5 papers), Sepsis Diagnosis and Treatment (5 papers), Electronic Health Records Systems (4 papers), Research Data Management Practices (3 papers) and Scientific Computing and Data Management (3 papers). The work is most often cited by research in Health Informatics (190 citations), Critical Care and Intensive Care Medicine (160 citations), Health Information Management (134 citations), Emergency Medicine (152 citations) and Pulmonary and Respiratory Medicine (406 citations). Tom Pollard has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Leo Anthony Celi, Alistair E. W. Johnson, David J. Stone, Rodrigo Octávio Deliberato, Dominic Charles Marshall, Justin D. Salciccioli, Roger G. Mark, Marco A. F. Pimentel, Marcus Josephus Schultz and Paolo P. Pelosi. Their work appears in journals such as Critical Care Medicine, Intensive Care Medicine, npj Digital Medicine, Journal of Medical Internet Research and The Lancet Digital Health.

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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