Mona Wanda Schmidt

48 papers receiving 1.0k citations

Mona Wanda Schmidt's Hit Papers

Machine Learning for Surgical Phase Recognition 2020 · 188 citations
1880+2+4Years since publication50100150

Peers

Mona Wanda Schmidt
Comparison fields: 5 of 93
  • Health Informatics 45
  • Surgery 542
  • Reproductive Medicine 60
  • Geriatrics and Gerontology 22
  • Obstetrics and Gynecology 35
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Jake Claflin United States
Karl‐Friedrich Kowalewski Germany
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Alvin C. Goh United States
Atul Kumar India
Amin Madani Canada
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Citations per field
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Citations per year

Countries citing papers authored by Mona Wanda Schmidt

Since Specialization
Citations

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

Fields of papers citing papers by Mona Wanda Schmidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mona Wanda Schmidt. 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 Mona Wanda Schmidt. The network helps show where Mona Wanda Schmidt may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 52 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Machine Learning for Surgical Phase Recognition
Hit paper breakdown →
2020188
2 202162
3 202058
4 201757
5 201957
6 201857
7 201654
8 201954
9 201750
10 201645
11 202034
12 201824
13 202224
14 202224
15 202122
16 202117
17 202215
18 202114
19 202214
20 201914

About Mona Wanda Schmidt

Mona Wanda Schmidt is a scholar working on Surgery, Reproductive Medicine, Public Health, Environmental and Occupational Health, Oncology and Obstetrics and Gynecology, having authored 52 papers that have together received 1.0k indexed citations. Recurring topics across this work include Surgical Simulation and Training (20 papers), Endometriosis Research and Treatment (6 papers), Pregnancy-related medical research (4 papers), Endometrial and Cervical Cancer Treatments (4 papers), Health, psychology, and well-being (3 papers), Frailty in Older Adults (3 papers), Pelvic floor disorders treatments (2 papers) and Lysosomal Storage Disorders Research (2 papers). The work is most often cited by research in Health Informatics (45 citations), Surgery (542 citations), Reproductive Medicine (60 citations), Geriatrics and Gerontology (22 citations) and Obstetrics and Gynecology (35 citations). Mona Wanda Schmidt has collaborated with scholars based in Germany, United States and Switzerland. Frequent co-authors include Felix Nickel, Beat P. Müller‐Stich, Karl‐Friedrich Kowalewski, Carly R. Garrow, Hannes Kenngott, Tanja Proctor, Sebastian Bodenstedt, Stefanie Speidel, Martin Wagner and Annette Hasenburg. Their work appears in journals such as Surgical Endoscopy, Journal of Clinical Medicine, International Journal of Environmental Research and Public Health, Archives of Gynecology and Obstetrics and Frontiers in Oncology.

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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