Serguei V S Pakhomov

Summary

Affiliation: Mayo Clinic
Country: USA

Publications

  1. ncbi Developing a corpus of clinical notes manually annotated for part-of-speech
    Serguei V Pakhomov
    Division of Biomedical Informatics, Mayo College of Medicine, Rochester, MN 55905, USA
    Int J Med Inform 75:418-29. 2006
  2. ncbi Automating the assignment of diagnosis codes to patient encounters using example-based and machine learning techniques
    Serguei V S Pakhomov
    Division of Biomedical Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
    J Am Med Inform Assoc 13:516-25. 2006
  3. ncbi Electronic medical records for clinical research: application to the identification of heart failure
    Serguei Pakhomov
    Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN 55905, USA
    Am J Manag Care 13:281-8. 2007
  4. ncbi The role of the electronic medical record in the assessment of health related quality of life
    Serguei V S Pakhomov
    Pharmaceutical Care and Health Systems, University of Minnesota, Minneapolis, MN, USA
    AMIA Annu Symp Proc 2011:1080-8. 2011
  5. ncbi A corpus driven approach applying the "frame semantic" method for modeling functional status terminology
    Alexander P Ruggieri
    Division of Medical Informatics Research, Department of Health Sciences Research, Harwick 826, Mayo Clinic, 200 SW First Street, Rochester, MN 55905, USA
    Stud Health Technol Inform 107:434-8. 2004
  6. ncbi Prospective recruitment of patients with congestive heart failure using an ad-hoc binary classifier
    Serguei V Pakhomov
    Division of Biomedical Informatics, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
    J Biomed Inform 38:145-53. 2005
  7. ncbi UMLS-Interface and UMLS-Similarity : open source software for measuring paths and semantic similarity
    Bridget T McInnes
    University of Minnesota, Minneapolis, MN, USA
    AMIA Annu Symp Proc 2009:431-5. 2009
  8. ncbi Automatic classification of foot examination findings using clinical notes and machine learning
    Serguei V S Pakhomov
    Department of Pharmaceutical Care and Health Systems, University of Minnesota, Twin Cities, MN, USA
    J Am Med Inform Assoc 15:198-202. 2008
  9. ncbi Using compound codes for automatic classification of clinical diagnoses
    Serguei V Pakhomov
    Division of Medical Informatics Research, Department of Health Sciences Research, Mayo Clinic, 200 SW First Street, Rochester, MN 55905, USA. Pakhomov.serguei @mayo.edu
    Medinfo 11:411-5. 2004
  10. ncbi Measures of semantic similarity and relatedness in the biomedical domain
    Ted Pedersen
    Department of Computer Science, 1114 Kirby Drive, University of Minnesota, Duluth, MN 55812, USA
    J Biomed Inform 40:288-99. 2007

Detail Information

Publications10

  1. ncbi Developing a corpus of clinical notes manually annotated for part-of-speech
    Serguei V Pakhomov
    Division of Biomedical Informatics, Mayo College of Medicine, Rochester, MN 55905, USA
    Int J Med Inform 75:418-29. 2006
    ..We describe and discuss the process of training three domain experts to perform linguistic annotation...
  2. ncbi Automating the assignment of diagnosis codes to patient encounters using example-based and machine learning techniques
    Serguei V S Pakhomov
    Division of Biomedical Informatics, Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
    J Am Med Inform Assoc 13:516-25. 2006
    ..Human classification of diagnoses is a labor intensive process that consumes significant resources. Most medical practices use specially trained medical coders to categorize diagnoses for billing and research purposes...
  3. ncbi Electronic medical records for clinical research: application to the identification of heart failure
    Serguei Pakhomov
    Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN 55905, USA
    Am J Manag Care 13:281-8. 2007
    ..To identify patients with heart failure (HF) by using language contained in the electronic medical record (EMR)...
  4. ncbi The role of the electronic medical record in the assessment of health related quality of life
    Serguei V S Pakhomov
    Pharmaceutical Care and Health Systems, University of Minnesota, Minneapolis, MN, USA
    AMIA Annu Symp Proc 2011:1080-8. 2011
    ..Our method represents an efficient and scalable surrogate measure of HRQOL to predict healthcare spending in ambulatory diabetes patients...
  5. ncbi A corpus driven approach applying the "frame semantic" method for modeling functional status terminology
    Alexander P Ruggieri
    Division of Medical Informatics Research, Department of Health Sciences Research, Harwick 826, Mayo Clinic, 200 SW First Street, Rochester, MN 55905, USA
    Stud Health Technol Inform 107:434-8. 2004
    ....
  6. ncbi Prospective recruitment of patients with congestive heart failure using an ad-hoc binary classifier
    Serguei V Pakhomov
    Division of Biomedical Informatics, Mayo Clinic College of Medicine, 200 First Street SW, Rochester, MN 55905, USA
    J Biomed Inform 38:145-53. 2005
    ..86%) but worse accuracy than Perceptron (57 vs. 65%). Both algorithms perform better than the baseline with recall on positive samples of 71% and accuracy of 54%...
  7. ncbi UMLS-Interface and UMLS-Similarity : open source software for measuring paths and semantic similarity
    Bridget T McInnes
    University of Minnesota, Minneapolis, MN, USA
    AMIA Annu Symp Proc 2009:431-5. 2009
    ..Our frameworks constitute a significant contribution to the field of biomedical Natural Language Processing by providing a common development and testing platform for semantic similarity measures based on the UMLS...
  8. ncbi Automatic classification of foot examination findings using clinical notes and machine learning
    Serguei V S Pakhomov
    Department of Pharmaceutical Care and Health Systems, University of Minnesota, Twin Cities, MN, USA
    J Am Med Inform Assoc 15:198-202. 2008
    ..This application may improve quality and safety by providing inexpensive and scalable methodology for quality and risk factor assessments at the point of care...
  9. ncbi Using compound codes for automatic classification of clinical diagnoses
    Serguei V Pakhomov
    Division of Medical Informatics Research, Department of Health Sciences Research, Mayo Clinic, 200 SW First Street, Rochester, MN 55905, USA. Pakhomov.serguei @mayo.edu
    Medinfo 11:411-5. 2004
    ..A small improvement (3%) with using compound categories over simple categories indicates that using multiple code categories is a promising solution, although clearly in need of further research and refinement...
  10. ncbi Measures of semantic similarity and relatedness in the biomedical domain
    Ted Pedersen
    Department of Computer Science, 1114 Kirby Drive, University of Minnesota, Duluth, MN 55812, USA
    J Biomed Inform 40:288-99. 2007
    ..We conclude that there is a role both for more flexible measures of relatedness based on information derived from corpora, as well as for measures that rely on existing ontological structures...