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Serguei V. S. Pakhomov

Serguei V. S. Pakhomov

D-Index & Metrics

Computer Science

D-Index
31
Citations
4570
World Ranking
13583
National Ranking
5424

Overview

Serguei V. S. Pakhomov is affiliated with the University of Minnesota in the United States. Their research primarily spans the field of Computer Science, with a focus on Artificial Intelligence. The scientist's work also intersects with Molecular Biology, Psychiatry and Mental Health, Cognitive Neuroscience, and Experimental and Cognitive Psychology.

The scholar has contributed to various domains, including:

  • Topic Modeling
  • Machine Learning in Healthcare
  • Biomedical Text Mining and Ontologies
  • Dementia and Cognitive Impairment Research
  • AI in Service Interactions
  • Emotion and Mood Recognition
  • Neurobiology of Language and Bilingualism

Their frequent co-authors include Trevor Cohen, Changye Li, Raymond Finzel, Greg Silverman, and Rui Zhang.

Publication venues where Serguei Pakhomov has appeared multiple times consist of:

  • arXiv (Cornell University)
  • Journal of Biomedical Informatics
  • Journal of the American Medical Informatics Association
  • PubMed
  • PLoS ONE

Recent papers by the scientist include:

  • "Are synthetic clinical notes useful for real natural language processing tasks: A case study on clinical entity recognition" (2021), published in Journal of the American Medical Informatics Association
  • "Using consumer-wearable technology for remote assessment of physiological response to stress in the naturalistic environment" (2020), published in PLoS ONE
  • "Crossing the "Cookie Theft" Corpus Chasm: Applying What BERT Learns From Outside Data to the ADReSS Challenge Dementia Detection Task" (2021), published in Frontiers in Computer Science
  • "NLP Methods for Extraction of Symptoms from Unstructured Data for Use in Prognostic COVID-19 Analytic Models" (2021), published in Journal of Artificial Intelligence Research
  • "Fully automated detection of formal thought disorder with Time-series Augmented Representations for Detection of Incoherent Speech (TARDIS)" (2022), published in Journal of Biomedical Informatics

Best Publications

  • Measures of semantic similarity and relatedness in the biomedical domain

    Ted Pedersen;Serguei V. S. Pakhomov;Siddharth Patwardhan;Christopher G. Chute

  • CLAMP - a toolkit for efficiently building customized clinical natural language processing pipelines.

    Ergin Soysal;Jingqi Wang;Min Jiang;Yonghui Wu

  • Agreement between patient-reported symptoms and their documentation in the medical record

    Serguei V. Pakhomov;Steven J. Jacobsen;Christopher G. Chute;Véronique L. Roger

  • Automating the assignment of diagnosis codes to patient encounters using example-based and machine learning techniques.

    Serguei V.S. Pakhomov;James D. Buntrock;Christopher G. Chute

  • Semantic Similarity and Relatedness between Clinical Terms: An Experimental Study

    Serguei Pakhomov;Bridget McInnes;Terrence Adam;Ying Liu

  • UMLS-Interface and UMLS-Similarity : open source software for measuring paths and semantic similarity.

    Bridget T. McInnes;Ted Pedersen;Serguei V.S. Pakhomov

  • Semi-Supervised Maximum Entropy Based Approach to Acronym and Abbreviation Normalization in Medical Texts.

    Sergey V. Pakhomov

  • Automated verbal fluency assessment

    Serguei V. S. Pakhomov;Laura Sue Hemmy;Kelvin O. Lim

  • Abbreviation and acronym disambiguation in clinical discourse.

    Serguei Pakhomov;Ted Pedersen;Christopher G. Chute

  • Corpus domain effects on distributional semantic modeling of medical terms.

    Serguei V. S. Pakhomov;Gregory P. Finley;Reed McEwan;Yan Wang

  • Towards a framework for developing semantic relatedness reference standards

    Serguei V.S. Pakhomov;Ted Pedersen;Bridget McInnes;Genevieve B. Melton

  • Developing a corpus of clinical notes manually annotated for part-of-speech

    Serguei V. S. Pakhomov;Anni Coden;Christopher G. Chute

  • Computerized analysis of speech and language to identify psycholinguistic correlates of frontotemporal lobar degeneration.

    Serguei V. S. Pakhomov;Glenn E. Smith;Dustin Chacon;Yara Feliciano

  • Domain-specific language models and lexicons for tagging

    Anni R. Coden;Serguei V. Pakhomov;Rie K. Ando;Patrick H. Duffy

  • Prospective recruitment of patients with congestive heart failure using an ad-hoc binary classifier

    Serguei V. Pakhomov;James Buntrock;Christopher G. Chute

  • Using semantic predications to uncover drug-drug interactions in clinical data

    Rui Zhang;Michael J. Cairelli;Marcelo Fiszman;Graciela Rosemblat

  • Semantic relatedness study using second order co-occurrence vectors computed from biomedical corpora, UMLS and WordNet

    Ying Liu;Bridget T. McInnes;Ted Pedersen;Genevieve Melton-Meaux

  • A computational linguistic measure of clustering behavior on semantic verbal fluency task predicts risk of future dementia in the nun study.

    Serguei V.S. Pakhomov;Laura S. Hemmy

  • A Comparative Study of Supervised Learning as Applied to Acronym Expansion in Clinical Reports

    Mahesh Joshi;Serguei V. S. Pakhomov;Ted Pedersen;Christopher G. Chute

  • Evaluating measures of redundancy in clinical texts

    Rui Zhang;Serguei Pakhomov;Bridget T. McInnes;Genevieve B. Melton

  • A sense inventory for clinical abbreviations and acronyms created using clinical notes and medical dictionary resources

    Sungrim Moon;Serguei V. S. Pakhomov;Nathan Liu;James O. Ryan

  • Computerized assessment of syntactic complexity in Alzheimer's disease: a case study of Iris Murdoch's writing.

    Serguei V Pakhomov;Dustin A Chacon;Mark Wicklund;Jeanette K Gundel

  • Using word embeddings to expand terminology of dietary supplements on clinical notes

    Yadan Fan;Serguei Pakhomov;Reed McEwan;Wendi Zhao

Frequent Co-Authors

Christopher G. Chute
Christopher G. Chute Johns Hopkins University
Ted Pedersen
Ted Pedersen University of Minnesota
David S. Knopman
David S. Knopman Mayo Clinic
Maria Gini
Maria Gini University of Minnesota
Hua Xu
Hua Xu Yale University
Ilo E. Leppik
Ilo E. Leppik University of Minnesota
Glenn E. Smith
Glenn E. Smith University of Florida
Xiaoqian Jiang
Xiaoqian Jiang The University of Texas Health Science Center at Houston
Thomas C. Rindflesch
Thomas C. Rindflesch National Institutes of Health

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