Matthew Withiam‐Leitch
- Public Health, Environmental and Occupational Health
- Obstetrics and Gynecology top 10%
- Sociology and Political Science
- Reproductive Medicine top 10%
- Safety Research top 10%
- Co-authors
- Alexander OlawaiyeAndrew B. SymonsDenise McGuiganElie A. AklNikhil SatchidanandJohn YehSameer GunukulaKunle Odunsi
- Topics
- Pancreatic function and diabetes (5 papers)Machine Learning in Healthcare (3 papers)Cellular transport and secretion (3 papers)
- Journals
- Journal of Biological ChemistryBiochemical and Biophysical Research CommunicationsMolecular Pharmacology
- Partner nations
- United StatesCanadaLebanon
In The Last Decade
Matthew Withiam‐Leitch
22 papers receiving 402 citations
Peers
Comparison fields: 5 of 96
- Public Health, Environmental and Occupational Health 104
- Obstetrics and Gynecology 83
- Sociology and Political Science 73
- Reproductive Medicine 71
- Safety Research 64
Countries citing papers authored by Matthew Withiam‐Leitch
This map shows the geographic impact of Matthew Withiam‐Leitch'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 Matthew Withiam‐Leitch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Withiam‐Leitch more than expected).
Fields of papers citing papers by Matthew Withiam‐Leitch
This network shows the impact of papers produced by Matthew Withiam‐Leitch. 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 Matthew Withiam‐Leitch. The network helps show where Matthew Withiam‐Leitch may publish in the future.
Co-authorship network of co-authors of Matthew Withiam‐Leitch
This figure shows the co-authorship network connecting the top 25 collaborators of Matthew Withiam‐Leitch. A scholar is included among the top collaborators of Matthew Withiam‐Leitch based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Matthew Withiam‐Leitch. Matthew Withiam‐Leitch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 1 | |
| 3 | 6 | |
| 4 | 25 | |
| 5 | 25 | |
| 6 | 105 | |
| 7 | 2 | |
| 8 | 36 | |
| 9 | 23 | |
| 10 | 37 | |
| 11 | Is there gender bias toward male residents in an obstetrics and gynecology training program? | 1 |
| 12 | 16 | |
| 13 | 16 | |
| 14 | 29 | |
| 15 | 26 | |
| 16 | 11 | |
| 17 | 2 | |
| 18 | 8 | |
| 19 | 5 | |
| 20 | 10 |
About Matthew Withiam‐Leitch
Matthew Withiam‐Leitch is a scholar working on Health Information Management, Obstetrics and Gynecology and Reproductive Medicine, having authored 22 papers that have together received 420 indexed citations. Recurring topics across this work include Pancreatic function and diabetes (5 papers), Machine Learning in Healthcare (3 papers) and Cellular transport and secretion (3 papers). The work is most often cited by research in Obstetrics and Gynecology (83 citations), Reproductive Medicine (71 citations) and Safety Research (64 citations). Matthew Withiam‐Leitch has collaborated with scholars based in United States, Canada and Lebanon. Frequent co-authors include Alexander Olawaiye, Andrew B. Symons, Denise McGuigan, Elie A. Akl, Nikhil Satchidanand, John Yeh, Sameer Gunukula, Kunle Odunsi, Shashikant Lele and Kenneth B. Kahn. Their work appears in journals such as Journal of Biological Chemistry, Biochemical and Biophysical Research Communications and Molecular Pharmacology.
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.