Maksim Belousov
- Applied Psychology top 10%
- Toxicology top 10%
- Pharmacovigilance and Adverse Drug Reactions 1
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- Social Media in Health Education 3
- Social Psychology top 10%
- Mental Health via Writing 2
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- Biomedical Text Mining and Ontologies 5
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- Topic Modeling 4
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- Health Literacy and Information Accessibility 2
- Mobile Health and mHealth Applications 1
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- Mental Health Research Topics 1
- Co-authors
- Goran NenadićNatalie BerryRichard EmsleySandra BucciFiona LobbanWilliam G DixonNabarun DasguptaMeghna Jani
- Cited by
- Applied PsychologyToxicologyHealth
- Journals
- Annals of the Rheumatic Diseases (1 paper)Journal of Medical Internet Research (1 paper)Journal of the American Medical Informatics Association (1 paper)
- Partner nations
- United KingdomUnited StatesSaudi Arabia
In The Last Decade
Maksim Belousov
11 papers receiving 275 citations
Peers
Comparison fields: 5 of 72
- Applied Psychology 64
- Toxicology 24
- Health 43
- Social Psychology 88
- Health Informatics 5
Countries citing papers authored by Maksim Belousov
This map shows the geographic impact of Maksim Belousov'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 Maksim Belousov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maksim Belousov more than expected).
Fields of papers citing papers by Maksim Belousov
This network shows the impact of papers produced by Maksim Belousov. 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 Maksim Belousov. The network helps show where Maksim Belousov may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Maksim Belousov, 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 | 2024 | 3 | |
| 2 | 2021 | 15 | |
| 3 | 2019 | 2 | |
| 4 | 2019 | 1 | |
| 5 | 2018 | 61 | |
| 6 | 2017 | 31 | |
| 7 | 2017 | 163 | |
| 8 | 2017 | 1 | |
| 9 | Using an Ensemble of Linear and Deep Learning Models in the SMM4H 2017 Medical Concept Normalisation Task. | 2017 | 4 |
| 10 | 2017 | 1 | |
| 11 | Mining Auditory Hallucinations from Unsolicited Twitter Posts | 2016 | 1 |
About Maksim Belousov
Maksim Belousov is a scholar working on Family Practice, Health and Toxicology, having authored 11 papers that have together received 283 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (5 papers), Topic Modeling (4 papers), Social Media in Health Education (3 papers), Mental Health via Writing (2 papers), Health Literacy and Information Accessibility (2 papers), Pharmacovigilance and Adverse Drug Reactions (1 paper), Mental Health Research Topics (1 paper) and Mobile Health and mHealth Applications (1 paper). The work is most often cited by research in Applied Psychology (64 citations), Toxicology (24 citations) and Health (43 citations). Maksim Belousov has collaborated with scholars based in United Kingdom, United States and Saudi Arabia. Frequent co-authors include Goran Nenadić, Natalie Berry, Richard Emsley, Sandra Bucci, Fiona Lobban, William G Dixon, Nabarun Dasgupta, Meghna Jani, Filip Ginter and Kai Hakala. Their work appears in journals such as Annals of the Rheumatic Diseases, Journal of Medical Internet Research and Journal of the American Medical Informatics Association.
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.