Modi Liu
Impact in
- Health Informatics top 5%
- Artificial Intelligence in Healthcare and Education
-
- Artificial Intelligence in Healthcare
Papers in
-
- Sepsis Diagnosis and Treatment 1
-
- Machine Learning in Healthcare 2
- AI in cancer detection 1
- Co-authors
- Minjie Xia (7 shared papers)Doff B. McElhinney (6 shared papers)Xuefeng B. Ling (7 shared papers)Eric Widen (7 shared papers)Shiying Hao (7 shared papers)Karl G. Sylvester (7 shared papers)Chengyin Ye (6 shared papers)Frank Stearns (5 shared papers)
- Journals
- Journal of Medical Internet Research (3 papers)International Journal of Medical Informatics (1 paper)Translational Psychiatry (1 paper)PLoS ONE (1 paper)International journal of medical and health sciences (1 paper)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Modi Liu
7 papers receiving 402 citations
Peers
Comparison fields: 5 of 81
- Health Informatics 43
- Health Information Management 66
- Physical Therapy, Sports Therapy and Rehabilitation 32
- Cardiology and Cardiovascular Medicine 62
- Artificial Intelligence 86
Countries citing papers authored by Modi Liu
This map shows the geographic impact of Modi Liu'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 Modi Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Modi Liu more than expected).
Fields of papers citing papers by Modi Liu
This network shows the impact of papers produced by Modi Liu. 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 Modi Liu. The network helps show where Modi Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Modi Liu, 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 | 2018 | 184 | |
| 2 | 2020 | 70 | |
| 3 | 2020 | 65 | |
| 4 | 2019 | 42 | |
| 5 | 2019 | 37 | |
| 6 | 2021 | 9 | |
| 7 | A Deep-Learning Based Prediction of Pancreatic Adenocarcinoma with Electronic Health Records from the State of Maine | 2020 | 4 |
About Modi Liu
Modi Liu is a scholar working on Epidemiology, Artificial Intelligence, Social Psychology, Cardiology and Cardiovascular Medicine and Clinical Psychology, having authored 7 papers that have together received 411 indexed citations. Recurring topics across this work include Machine Learning in Healthcare (2 papers), Heart Failure Treatment and Management (1 paper), Pancreatic and Hepatic Oncology Research (1 paper), Cardiac Arrest and Resuscitation (1 paper), Suicide and Self-Harm Studies (1 paper), Balance, Gait, and Falls Prevention (1 paper), AI in cancer detection (1 paper) and Sepsis Diagnosis and Treatment (1 paper). The work is most often cited by research in Health Informatics (43 citations), Health Information Management (66 citations), Physical Therapy, Sports Therapy and Rehabilitation (32 citations), Cardiology and Cardiovascular Medicine (62 citations) and Artificial Intelligence (86 citations). Modi Liu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Minjie Xia, Doff B. McElhinney, Xuefeng B. Ling, Eric Widen, Shiying Hao, Karl G. Sylvester, Chengyin Ye, Frank Stearns, Bo Jin and Oliver Wang. Their work appears in journals such as Journal of Medical Internet Research, International Journal of Medical Informatics, Translational Psychiatry, PLoS ONE and International journal of medical and health sciences.
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.