Mia Levy

99 papers receiving 2.1k citations

Peers

Mia Levy
Comparison fields: 5 of 134
  • Health Information Management 145
  • Cancer Research 332
  • Health Informatics 30
  • Oncology 490
  • Immunology 347
Replace Jeremy L. Warner with:
Jeremy L. Warner United States
Michael J. Becich United States
Sean Khozin United States
Kenneth Jung United States
Subha Madhavan United States
Sharyl J. Nass United States
K. Stephen Suh United States
Michael J. Hassett United States
D.M. Jukic United States
Turgay Ayer United States
Mia Levy relative to Jeremy L. Warner United States Jeremy L. Warner's profile →
Citations per field
00.5×4.2×
Jeremy L. Warner · 1×
Citations per year

Countries citing papers authored by Mia Levy

Since Specialization
Citations

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

Fields of papers citing papers by Mia Levy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 103 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010400
2 2013201
3 2014171
4 201390
5 201268
6
Extracting and integrating data from entire electronic health records for detecting colorectal cancer cases.
201165
7 201659
8 201657
9 201451
10 201749
11 202249
12 201942
13 201340
14 202235
15 201033
16 201833
17 199827
18 201626
19
Tool support to enable evaluation of the clinical response to treatment.
200826
20
Medical admissions due to noncompliance with drug therapy.
198226

About Mia Levy

Mia Levy is a scholar working on Molecular Biology, Oncology, Cancer Research, Pulmonary and Respiratory Medicine and Artificial Intelligence, having authored 103 papers that have together received 2.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (15 papers), Radiomics and Machine Learning in Medical Imaging (9 papers), BRCA gene mutations in cancer (6 papers), Biomedical Text Mining and Ontologies (6 papers), Advanced Breast Cancer Therapies (5 papers), Prostate Cancer Treatment and Research (4 papers), Medication Adherence and Compliance (4 papers) and Semantic Web and Ontologies (4 papers). The work is most often cited by research in Health Information Management (145 citations), Cancer Research (332 citations), Health Informatics (30 citations), Oncology (490 citations) and Immunology (347 citations). Mia Levy has collaborated with scholars based in United States, United Kingdom and Italy. Frequent co-authors include Joshua C. Denny, Thomas A. Lasko, Jeremy L. Warner, Christine M. Lovly, Daniel L. Rubin, Christine Micheel, Youn H. Kim, Lewis K. Shin, Richard T. Hoppe and Irene Wapnir. Their work appears in journals such as Journal of Clinical Oncology, JCO Clinical Cancer Informatics, Journal of the American Medical Informatics Association, The Oncologist and Breast Cancer Research and Treatment.

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.

Explore authors with similar magnitude of impact