Dmitriy Dligach
- Health Informatics top 1%
- Artificial Intelligence top 1%
- Topic Modeling 54
- Natural Language Processing Techniques 37
- Machine Learning in Healthcare 25
- Neurology top 5%
- Intracranial Aneurysms: Treatment and Complications 19
- Traumatic Brain Injury and Neurovascular Disturbances 8
- Rheumatology top 10%
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- Biomedical Text Mining and Ontologies 29
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- Cerebrovascular and Carotid Artery Diseases 10
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- Opioid Use Disorder Treatment 7
- Co-authors
- Guergana SavovaTimothy A. MillerMartha PalmerSameer PradhanSteven BethardChen LinMajid AfsharEdward Loper
- Journals
- Journal of the American Medical Informatics Association (15 papers)Scientific Reports (5 papers)Journal of Biomedical Informatics (4 papers)
- Partner nations
- United StatesChinaNetherlands
In The Last Decade
Dmitriy Dligach
97 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 120
- Health Informatics 136
- Artificial Intelligence 1.2k
- Health Information Management 125
- Neurology 356
- Rheumatology 112
Countries citing papers authored by Dmitriy Dligach
This map shows the geographic impact of Dmitriy Dligach'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 Dmitriy Dligach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dmitriy Dligach more than expected).
Fields of papers citing papers by Dmitriy Dligach
This network shows the impact of papers produced by Dmitriy Dligach. 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 Dmitriy Dligach. The network helps show where Dmitriy Dligach may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Dmitriy Dligach, 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 | 1 | |
| 2 | 2025 | 1 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 1 | |
| 5 | 2024 | 0 | |
| 6 | 2024 | 15 | |
| 7 | 2024 | 2 | |
| 8 | 2024 | 3 | |
| 9 | 2024 | 2 | |
| 10 | 2023 | 6 | |
| 11 | 2023 | 8 | |
| 12 | 2023 | 14 | |
| 13 | 2023 | 12 | |
| 14 | 2022 | 12 | |
| 15 | 2022 | 2 | |
| 16 | 2021 | 2 | |
| 17 | 2020 | 2 | |
| 18 | 2017 | 65 | |
| 19 | 2017 | 10 | |
| 20 | Discovering Body Site and Severity Modifiers in Clinical Texts. | 2013 | 1 |
About Dmitriy Dligach
Dmitriy Dligach is a scholar working on Health Informatics, Artificial Intelligence and Family Practice, having authored 106 papers that have together received 2.0k indexed citations. Recurring topics across this work include Topic Modeling (54 papers), Natural Language Processing Techniques (37 papers), Biomedical Text Mining and Ontologies (29 papers), Machine Learning in Healthcare (25 papers), Intracranial Aneurysms: Treatment and Complications (19 papers), Cerebrovascular and Carotid Artery Diseases (10 papers), Traumatic Brain Injury and Neurovascular Disturbances (8 papers) and Opioid Use Disorder Treatment (7 papers). The work is most often cited by research in Health Informatics (136 citations), Artificial Intelligence (1.2k citations) and Health Information Management (125 citations). Dmitriy Dligach has collaborated with scholars based in United States, China and Netherlands. Frequent co-authors include Guergana Savova, Timothy A. Miller, Martha Palmer, Sameer Pradhan, Steven Bethard, Chen Lin, Majid Afshar, Edward Loper, Vivian S. Gainer and Nancy A. Shadick. Their work appears in journals such as Journal of the American Medical Informatics Association, Scientific Reports, Journal of Biomedical Informatics, Stroke and Neurology.
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.