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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Collaborations and top research areas from the last five years
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Maintenance of a chatbot for training certified assessors
Pakhomov, S. V. (PI)
MN DEPARTMENT OF HUMAN SERVICES
7/1/24 → 6/30/25
Project: Research project
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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 NAT'L 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)
6/30/22 → 2/28/25
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)
6/1/22 → 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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Predicting accrual success for better clinical trial resource allocation
Ma, S., Wang, Y., Wagner, J., Johnson, S., Pakhomov, S. V. & Aliferis, C., Dec 2025, In: Scientific reports. 15, 1, 3879.Research output: Contribution to journal › Article › peer-review
Open Access -
A conversational agent for early detection of neurotoxic effects of medications through automated intensive observation
Pakhomov, S., Solinsky, J., Michalowski, M. & Bachanova, V., 2024, Pacific Symposium on Biocomputing 2024, PSB 2024. Altman, R. B., Hunter, L., Ritchie, M. D., Murray, T. & Klein, T. E. (eds.). 2024 ed. World Scientific, p. 24-38 15 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Scopus citations -
A curious case of retrogenesis in language: Automated analysis of language patterns observed in dementia patients and young children
Li, C., Solinsky, J. C., Cohen, T. & Pakhomov, S., Mar 2024, In: Neuroscience Informatics. 4, 1, 100155.Research output: Contribution to journal › Article › peer-review
Open Access1 Scopus citations -
Too Big to Fail: Larger Language Models are Disproportionately Resilient to Induction of Dementia-Related Linguistic Anomalies
Li, C., Sheng, Z., Cohen, T. & Pakhomov, S., 2024, 62nd Annual Meeting of the Association for Computational Linguistics, ACL 2024 - Proceedings of the Conference. Ku, L.-W., Martins, A. & Srikumar, V. (eds.). Association for Computational Linguistics (ACL), p. 6363-6377 15 p. (Proceedings of the Annual Meeting of the Association for Computational Linguistics).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
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