Craig H. Mermel
- Cancer Research top 0.2%
- Cancer Genomics and Diagnostics 6
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education 4
- Oncology top 1%
- Colorectal Cancer Screening and Detection 5
- Molecular Biology top 1%
- Molecular Biology Techniques and Applications 2
- Epigenetics and DNA Methylation 2
- Genetics top 1%
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- Radiomics and Machine Learning in Medical Imaging 12
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- AI in cancer detection 11
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- Lung Cancer Treatments and Mutations 4
- Co-authors
- Matthew MeyersonGad GetzRameen BeroukhimSteven E. SchumacherBarbara HillStacey GabrielMichael S. LawrenceTodd R. Golub
- Partner nations
- United StatesAustriaUnited Kingdom
In The Last Decade
Craig H. Mermel
31 papers receiving 7.9k citations
Hit Papers
Peers
Comparison fields: 5 of 146
- Cancer Research 3.0k
- Health Informatics 188
- Oncology 2.1k
- Molecular Biology 4.5k
- Genetics 603
Countries citing papers authored by Craig H. Mermel
This map shows the geographic impact of Craig H. Mermel'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 Craig H. Mermel with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Craig H. Mermel more than expected).
Fields of papers citing papers by Craig H. Mermel
This network shows the impact of papers produced by Craig H. Mermel. 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 Craig H. Mermel. The network helps show where Craig H. Mermel may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Craig H. Mermel, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 3 | |
| 2 | 2023 | 12 | |
| 3 | 2021 | 34 | |
| 4 | 2021 | 86 | |
| 5 | 2021 | 33 | |
| 6 | 2020 | 51 | |
| 7 | 2020 | 159 | |
| 8 | Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancerbreakdown → | 2019 | 302 |
| 9 | 2019 | 122 | |
| 10 | 2019 | 186 | |
| 11 | 2015 | 59 | |
| 12 | Discovery and saturation analysis of cancer genes across 21 tumour typesbreakdown → | 2014 | 2059 |
| 13 | Pan-cancer patterns of somatic copy number alterationbreakdown → | 2013 | 1243 |
| 14 | 2012 | 127 | |
| 15 | 2012 | 29 | |
| 16 | 2012 | 15 | |
| 17 | GISTIC2.0 facilitates sensitive and confident localization of the targets of focal somatic copy-number alteration in human cancersbreakdown → | 2011 | 2008 |
| 18 | 2011 | 296 | |
| 19 | 2010 | 90 | |
| 20 | 2009 | 77 |
About Craig H. Mermel
Craig H. Mermel is a scholar working on Health Informatics, Radiology, Nuclear Medicine and Imaging and Cancer Research, having authored 31 papers that have together received 8.0k indexed citations. Recurring topics across this work include Radiomics and Machine Learning in Medical Imaging (12 papers), AI in cancer detection (11 papers), Cancer Genomics and Diagnostics (6 papers), Colorectal Cancer Screening and Detection (5 papers), Artificial Intelligence in Healthcare and Education (4 papers), Lung Cancer Treatments and Mutations (4 papers), Molecular Biology Techniques and Applications (2 papers) and Epigenetics and DNA Methylation (2 papers). The work is most often cited by research in Cancer Research (3.0k citations), Health Informatics (188 citations) and Oncology (2.1k citations). Craig H. Mermel has collaborated with scholars based in United States, Austria and United Kingdom. Frequent co-authors include Matthew Meyerson, Gad Getz, Rameen Beroukhim, Steven E. Schumacher, Barbara Hill, Stacey Gabriel, Michael S. Lawrence, Todd R. Golub, Eric S. Lander and Petar Stojanov. Their work appears in journals such as PLoS ONE, Blood, npj Digital Medicine, Scientific Reports and Nature Genetics.
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.