M.S. Leaning

1.1k citations
38 papers · 857 · h-index 15

Impact in

Papers in

M.S. Leaning

37 papers receiving 792 citations

Peers

M.S. Leaning
Comparison fields: 5 of 145
  • Health Information Management 74
  • Cardiology and Cardiovascular Medicine 213
  • Nephrology 44
  • Software 24
  • Surgery 177
Replace Jack D. Myers with:
Jack D. Myers United States
Derek G. Cramp United Kingdom
Jos L. Willems Belgium
Anushya Vijayananthan Malaysia
Bert de Brock Netherlands
Jari Forsström Finland
Desmond A. Jordan United States
Artur Akbarov United Kingdom
H. R. Warner United States
Kazunobu Yamauchi Japan
M.S. Leaning relative to Jack D. Myers United States Jack D. Myers's profile →
Citations per field
00.5×2×3×4×4.9×
Jack D. Myers · 1×
Citations per year

Countries citing papers authored by M.S. Leaning

Since Specialization
Citations

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

Fields of papers citing papers by M.S. Leaning

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M.S. Leaning. 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 M.S. Leaning. The network helps show where M.S. Leaning may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1984143
2 1984108
3 200878
4 199771
5 198463
6 198350
7 198543
8 201542
9 199731
10 199121
11 201218
12
Validation of an algorithm for oral anticoagulant dosing and appointment scheduling.
199518
13 199618
14 198517
15 198316
16 199215
17 199213
18 199013
19 198712
20 19886

About M.S. Leaning

M.S. Leaning is a scholar working on Health Information Management, Surgery, Artificial Intelligence, Cardiology and Cardiovascular Medicine and Computational Theory and Mathematics, having authored 38 papers that have together received 857 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (4 papers), Electronic Health Records Systems (4 papers), Healthcare Technology and Patient Monitoring (4 papers), AI-based Problem Solving and Planning (3 papers), Logic, Reasoning, and Knowledge (3 papers), Hemodynamic Monitoring and Therapy (3 papers), Control Systems and Identification (3 papers) and Heart Rate Variability and Autonomic Control (3 papers). The work is most often cited by research in Health Information Management (74 citations), Cardiology and Cardiovascular Medicine (213 citations), Nephrology (44 citations), Software (24 citations) and Surgery (177 citations). M.S. Leaning has collaborated with scholars based in United Kingdom, United States and Finland. Frequent co-authors include L. Finkelstein, William Geoffrey Parkin, Bipin Vadher, Ewart R. Carson, David L. Patterson, Claudio Cobelli, Sören Söndergaard, Derek G. Cramp, Massoud A. Boroujerdi and J.A. Bushman. Their work appears in journals such as Measurement, Computer Methods and Programs in Biomedicine, Journal of Hepatology, Intensive Care Medicine and American Journal of Physiology-Regulatory, Integrative and Comparative Physiology.

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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