Projects per year
Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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The Fingerprint is created by mining the titles and abstracts of the person's research outputs and projects/funding awards to create an index of weighted terms from discipline-specific thesauri.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Developing Data-Driven Clinical Signatures for People who Experience Hallucinations
Pakhomov, S. V. (PI) & Michalowski, M. (CoI)
UNIVERSITY OF WASHINGTON, NATIONAL INSTITUTES OF HEALTH (NIH)
4/2/24 → 1/31/29
Project: Research project
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University of Minnesota Clinical and Translational Science Institute (UMN CTSI)
Blazar, B. R. (PI), Beebe, T. J. (CoI), Bellin, M. D. (CoI), Berge, J. M. (CoI), Billings, J. L. (CoI), Bischof, J. C. (CoI), Brearley, A. M. (CoI), Call, K. T. (CoI), Fu, S. S. (CoI), Fulkerson, J. (CoI), Guan, W. (CoI), Hardeman, R. R. (CoI), Haynes, D. A. (CoI), Henning-Smith, C. E. (CoI), Johnson, S. (CoI), Jones-Webb, R. J. (CoI), Kozhimannil, K. B. (CoI), Langworthy, B. (CoI), Lim, H. H. (CoI), Melton-Meaux, G. B. (CoI), Nunez, A. (CoI), Pakhomov, S. V. (CoI), Pieczkiewicz, D. S. (CoI), Randolph, A. C. (CoI), Riggs, S. (CoI), Rudser, K. (CoI), Schleiss, M. R. (CoI), Shen, S. (CoI), Vaughn, B. P. (CoI) & Vock, D. M. (CoI)
NIH NATL CTR FOR ADVANCING TRAN SCIENCE
9/18/23 → 7/31/30
Project: Research project
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DeconDTN: Deconfounding Deep Transformer Networks for Clinical NLP
Pakhomov, S. V. (PI)
UNIVERSITY OF WASHINGTON, NATIONAL INSTITUTES OF HEALTH (NIH)
6/1/22 → 2/28/26
Project: Research project
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Maintenance of a chatbot for training certified assessors
Pakhomov, S. V. (PI)
MINNESOTA DEPARTMENT OF HUMAN SERVICES
7/1/24 → 6/30/25
Project: Research project
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DeconDTN: Deconfounding Deep Transformer Networks for Clinical NLP
Pakhomov, S. V. (PI)
UNIVERSITY OF WASHINGTON, NATIONAL INSTITUTES OF HEALTH (NIH)
6/30/22 → 2/28/25
Project: Research project
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Coherence and comprehensibility: Large language models predict lay understanding of health-related content
Cohen, T., Xu, W., Guo, Y., Pakhomov, S. & Leroy, G., Jan 2025, In: Journal of Biomedical Informatics. 161, 104758.Research output: Contribution to journal › Article › peer-review
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Decoding nature’s grammar with DNA language models
Morrell, P. L. & Pakhomov, S. V., Jul 22 2025, In: Proceedings of the National Academy of Sciences of the United States of America. 122, 29, e2512889122.Research output: Contribution to journal › Comment/debate › peer-review
Open Access -
Mitigating Confounding in Speech-Based Dementia Detection through Weight Masking
Sheng, Z., Ding, X., Hur, B., Li, C., Cohen, T. & Pakhomov, S., 2025, Long Papers. Che, W., Nabende, J., Shutova, E. & Pilehvar, M. T. (eds.). Association for Computational Linguistics (ACL), p. 10419-10434 16 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics; vol. 1).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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Perplexity and proximity: Large language model perplexity complements semantic distance metrics for the detection of incoherent speech
Xu, W., Pakhomov, S., Heagerty, P., Horvitz, E., Bradley, E. R., Woolley, J., Campbell, A., Cohen, A., Ben-Zeev, D. & Cohen, T., Oct 2025, In: Journal of Biomedical Informatics. 170, 104899.Research output: Contribution to journal › Article › peer-review
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Predicting accrual success for better clinical trial resource allocation
Ma, S., Wang, Y., Wagner, J., Johnson, S., Pakhomov, S. & Aliferis, C., Dec 2025, In: Scientific reports. 15, 1, 3879.Research output: Contribution to journal › Article › peer-review
Open Access
Datasets
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Semantic Relatedness and Similarity Reference Standards for Medical Terms
Pakhomov, S., Data Repository for the University of Minnesota, 2018
DOI: 10.13020/D6CX04, http://hdl.handle.net/11299/196265
Dataset