Piyush Mathur

22 papers receiving 571 citations

Piyush Mathur's Hit Papers

A framework for human evaluation of large language models in healthcare derived from literature review 2024 · 101 citations
1010+1+2Years since publication50100150200250

Peers

Piyush Mathur
Comparison fields: 5 of 111
  • Health Informatics 254
  • Health Information Management 52
  • Safety Research 45
  • Family Practice 8
  • Medical Laboratory Technology 6
Replace Milap Shah with:
Milap Shah India
Michaela Hardt United States
Danielle Whicher United States
Sonoo Thadaney-Israni United States
Armando Bedoya United States
Fred Hersch Australia
Ahmed Al Kuwaiti Saudi Arabia
Shalmali Joshi United States
Mjaye Mazwi Canada
David Lyell Australia
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Countries citing papers authored by Piyush Mathur

Since Specialization
Citations

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

Fields of papers citing papers by Piyush Mathur

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Bias in artificial intelligence algorithms and recommendations for mitigation
Hit paper breakdown →
2023279
2 2021110
3
A framework for human evaluation of large language models in healthcare derived from literature review
Hit paper breakdown →
2024101
4 201327
5 201921
6 202013
7 20198
8 20187
9 20256
10 20156
11 20244
12 20084
13 20133
14 20143
15 20232
16 20252
17 20252
18 20182
19 20251
20 20211

About Piyush Mathur

Piyush Mathur is a scholar working on Health Informatics, Surgery, Pulmonary and Respiratory Medicine, Artificial Intelligence and Radiology, Nuclear Medicine and Imaging, having authored 34 papers that have together received 605 indexed citations. Recurring topics across this work include Artificial Intelligence in Healthcare and Education (10 papers), Central Venous Catheters and Hemodialysis (3 papers), Respiratory Support and Mechanisms (2 papers), Machine Learning in Healthcare (2 papers), Electronic Health Records Systems (2 papers), Muscle and Compartmental Disorders (2 papers), Artificial Intelligence in Healthcare (2 papers) and COVID-19 and healthcare impacts (2 papers). The work is most often cited by research in Health Informatics (254 citations), Health Information Management (52 citations), Safety Research (45 citations), Family Practice (8 citations) and Medical Laboratory Technology (6 citations). Piyush Mathur has collaborated with scholars based in United States, India and United Kingdom. Frequent co-authors include Ashish K. Khanna, Dana Moukheiber, Mira Moukheiber, Lama Moukheiber, Lama Nazer, Rachel Hicklen, Janny Xue Chen Ke, Haobo Ma, Michael Burns and Markus Wenzel. Their work appears in journals such as Journal of Plastic Reconstructive & Aesthetic Surgery, Critical Care Medicine, Journal of Anaesthesiology Clinical Pharmacology, Journal of Clinical Monitoring and Computing and Journal of Clinical Anesthesia.

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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