He Ma
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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- Lung Cancer Diagnosis and Treatment 8
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- Radiomics and Machine Learning in Medical Imaging 6
- COVID-19 diagnosis using AI 2
- Co-authors
- Wei Qian (5 shared papers)Shouliang Qi (3 shared papers)Yudong Yao (3 shared papers)Patrice Monkam (1 shared paper)Weiming Gao (1 shared paper)Li Liu (2 shared papers)Chuanfu Li (2 shared papers)Hongyang Jiang (3 shared papers)
- Journals
- Medical Physics (1 paper)The FASEB Journal (1 paper)IEEE Access (1 paper)JAMA Network Open (1 paper)Journal of Pharmacy and Pharmacology (1 paper)
- Partner nations
- ChinaUnited StatesNetherlands
In The Last Decade
He Ma
13 papers receiving 437 citations
Peers
Comparison fields: 5 of 75
- Radiology, Nuclear Medicine and Imaging 183
- Pulmonary and Respiratory Medicine 150
- Health Informatics 6
- Obstetrics and Gynecology 24
- Artificial Intelligence 70
Countries citing papers authored by He Ma
This map shows the geographic impact of He Ma'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 He Ma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites He Ma more than expected).
Fields of papers citing papers by He Ma
This network shows the impact of papers produced by He Ma. 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 He Ma. The network helps show where He Ma may publish in the future.
Co-authors
The 25 scholars most cited alongside He Ma, 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 | 2017 | 130 | |
| 2 | 2019 | 90 | |
| 3 | 2020 | 68 | |
| 4 | 2016 | 57 | |
| 5 | 2019 | 48 | |
| 6 | 2015 | 24 | |
| 7 | 2017 | 11 | |
| 8 | 2022 | 8 | |
| 9 | Lung Cancer Detection and Analysis Using Data Mining Techniques, Principal Component Analysis and Artificial Neural Network | 2016 | 4 |
| 10 | 2017 | 4 | |
| 11 | 2025 | 2 | |
| 12 | 2025 | 1 | |
| 13 | 2017 | 1 |
About He Ma
He Ma is a scholar working on Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging, Epidemiology, Molecular Biology and Cardiology and Cardiovascular Medicine, having authored 13 papers that have together received 448 indexed citations. Recurring topics across this work include Lung Cancer Diagnosis and Treatment (8 papers), Radiomics and Machine Learning in Medical Imaging (6 papers), COVID-19 diagnosis using AI (2 papers), Peroxisome Proliferator-Activated Receptors (1 paper), Pharmacological Effects of Natural Compounds (1 paper), Endometrial and Cervical Cancer Treatments (1 paper), Lipid metabolism and disorders (1 paper) and Autophagy in Disease and Therapy (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (183 citations), Pulmonary and Respiratory Medicine (150 citations), Health Informatics (6 citations), Obstetrics and Gynecology (24 citations) and Artificial Intelligence (70 citations). He Ma has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Wei Qian, Shouliang Qi, Yudong Yao, Patrice Monkam, Weiming Gao, Li Liu, Chuanfu Li, Hongyang Jiang, Xiaohui Wang and Tuanzhu Ha. Their work appears in journals such as Medical Physics, The FASEB Journal, IEEE Access, JAMA Network Open and Journal of Pharmacy and Pharmacology.
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.