Maren E. Shipe

15 papers receiving 330 citations

Maren E. Shipe's Hit Papers

Developing prediction models for clinical use using logistic regression: an overview 2019 · 276 citations
2760+2+4Years since publication50100150200250

Peers

Maren E. Shipe
Comparison fields: 5 of 119
  • Health Informatics 9
  • Health Information Management 28
  • Medical Laboratory Technology 4
  • Radiology, Nuclear Medicine and Imaging 54
  • Transplantation 6
Replace Justin Slater with:
Justin Slater Canada
Laura Ruth Venable United States
Shusuke Hiragi Japan
Christina Catley Canada
Aditi Gupta United States
Nianzong Hou China
Rafael García Carretero Spain
Mustafa Khanbhai United Kingdom
Hyo Kyung Lee United States
Erik Korsten Netherlands
Maren E. Shipe relative to Justin Slater Canada Justin Slater's profile →
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Countries citing papers authored by Maren E. Shipe

Since Specialization
Citations

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

Fields of papers citing papers by Maren E. Shipe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Maren E. Shipe. 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 Maren E. Shipe. The network helps show where Maren E. Shipe may publish in the future.

Co-authors

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

All Works

16 of 16 papers shown
#Work
1
Developing prediction models for clinical use using logistic regression: an overview
Hit paper breakdown →
2019276
2 20209
3 20209
4 20208
5 20155
6 20214
7 20204
8 20203
9 20203
10 20213
11 20233
12 20203
13 20222
14 20241
15 20201
16 20250

About Maren E. Shipe

Maren E. Shipe is a scholar working on Pulmonary and Respiratory Medicine, Surgery, Oncology, Radiology, Nuclear Medicine and Imaging and Cardiology and Cardiovascular Medicine, having authored 16 papers that have together received 334 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (5 papers), Lung Cancer Treatments and Mutations (3 papers), COVID-19 and healthcare impacts (3 papers), Pleural and Pulmonary Diseases (2 papers), Hepatitis C virus research (2 papers), Renal Transplantation Outcomes and Treatments (2 papers), Esophageal and GI Pathology (2 papers) and Radiomics and Machine Learning in Medical Imaging (2 papers). The work is most often cited by research in Health Informatics (9 citations), Health Information Management (28 citations), Medical Laboratory Technology (4 citations), Radiology, Nuclear Medicine and Imaging (54 citations) and Transplantation (6 citations). Maren E. Shipe has collaborated with scholars based in United States. Frequent co-authors include Stephen A. Deppen, Eric L. Grogan, Farhood Farjah, Diane N. Haddad, Benjamin D. Kozower, Erin A. Gillaspie, Amelia W. Maiga, David O. Wilson, Michael N. Kammer and Babette S. Saltzman. Their work appears in journals such as The Annals of Thoracic Surgery, Journal of Thoracic and Cardiovascular Surgery, The American Surgeon, Surgical Endoscopy and The Cleft Palate-Craniofacial Journal.

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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