Nancy Diao
Impact in
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- Radiomics and Machine Learning in Medical Imaging
- COVID-19 diagnosis using AI
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- Lung Cancer Diagnosis and Treatment
Papers in
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- Health, Environment, Cognitive Aging 2
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- Pesticide Exposure and Toxicity 3
- Co-authors
- D Christiani (9 shared papers)Michael D. Lanuti (1 shared paper)Andrea T. Shafer (1 shared paper)Tafadzwa Lawrence Chaunzwa (1 shared paper)Yiwen Xu (1 shared paper)Hugo J.W.L. Aerts (1 shared paper)Ahmed Hosny (1 shared paper)Raymond H. Mak (1 shared paper)
- Journals
- PLoS ONE (3 papers)Lung Cancer (2 papers)Scientific Reports (1 paper)Molecular Human Reproduction (1 paper)Genetic Epidemiology (1 paper)
- Partner nations
- United StatesChinaUnited Kingdom
In The Last Decade
Nancy Diao
13 papers receiving 412 citations
Nancy Diao's Hit Papers
Peers
Comparison fields: 5 of 59
- Radiology, Nuclear Medicine and Imaging 140
- Pulmonary and Respiratory Medicine 122
- Health Informatics 6
- Health, Toxicology and Mutagenesis 53
- Artificial Intelligence 87
Countries citing papers authored by Nancy Diao
This map shows the geographic impact of Nancy Diao'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 Nancy Diao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nancy Diao more than expected).
Fields of papers citing papers by Nancy Diao
This network shows the impact of papers produced by Nancy Diao. 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 Nancy Diao. The network helps show where Nancy Diao may publish in the future.
Co-authors
The 25 scholars most cited alongside Nancy Diao, 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 | Deep learning classification of lung cancer histology using CT images Hit paper breakdown → | 2021 | 186 |
| 2 | 2019 | 63 | |
| 3 | 2014 | 45 | |
| 4 | 2014 | 27 | |
| 5 | 2014 | 26 | |
| 6 | 2017 | 23 | |
| 7 | 2023 | 13 | |
| 8 | 2021 | 12 | |
| 9 | 2019 | 12 | |
| 10 | 2012 | 10 | |
| 11 | 2022 | 2 | |
| 12 | 2012 | 2 | |
| 13 | 2022 | 1 | |
| 14 | 2016 | 0 |
About Nancy Diao
Nancy Diao is a scholar working on Health, Toxicology and Mutagenesis, Plant Science, Genetics, Pulmonary and Respiratory Medicine and Reproductive Medicine, having authored 14 papers that have together received 422 indexed citations. Recurring topics across this work include Gene expression and cancer classification (3 papers), Pesticide Exposure and Toxicity (3 papers), Lung Cancer Diagnosis and Treatment (2 papers), Health, Environment, Cognitive Aging (2 papers), Genetic Associations and Epidemiology (2 papers), Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities (1 paper), Advanced Causal Inference Techniques (1 paper) and Sperm and Testicular Function (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (140 citations), Pulmonary and Respiratory Medicine (122 citations), Health Informatics (6 citations), Health, Toxicology and Mutagenesis (53 citations) and Artificial Intelligence (87 citations). Nancy Diao has collaborated with scholars based in United States, China and United Kingdom. Frequent co-authors include D Christiani, Michael D. Lanuti, Andrea T. Shafer, Tafadzwa Lawrence Chaunzwa, Yiwen Xu, Hugo J.W.L. Aerts, Ahmed Hosny, Raymond H. Mak, Maitreyi Mazumdar and Quazi Quamruzzaman. Their work appears in journals such as PLoS ONE, Lung Cancer, Scientific Reports, Molecular Human Reproduction and Genetic Epidemiology.
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.