Publications

Our team relies on over 10 years of research and experience in healthcare related information technology to provide state-of-the-art customized solutions for clinical information needs of our clients. We strive to share the results of our research with the community through publication in journals and conference proceedings.

Selected Key Publications

  1. Bursi, F., Weston, SA., Redfield, MM., Jacobsen, SJ., Pakhomov, S., Nkomo, VT., Meverden, RA., & Roger, VL. (2006) Systolic and Diastolic Heart Failure in the Community. JAMA 2006; 296(18):2209-2216. Abstract
  2. Pakhomov, S., Hemingway, H., Weston, S., Jacobsen, S., Rodeheffer, R., & Roger, V. (2007). Epidemiology of Angina Pectoris: Role of Natural Language Processing of the Medical Record. American Heart Journal 2007; 153(4):666-673. Abstract
  3. Pakhomov, S., Weston, S., Jacobsen, S., Chute, C., Meverden, R., & Roger, V. (2007). Electronic Medical Records for Clinical Research: Application to the Identification of Heart Failure. American Journal of Managed Care, 2007; 13:281-288. Abstract
  4. Pakhomov, S., Jacobsen, S., Chute, C., & Roger, V. (2008). Agreement between Patient-reported Symptoms and their Documentation in the Medical Record. American Journal of Managed Care, 14(8):530-539. Abstract
  5. Pakhomov, S., Buntrock, J., & Chute, CG. (2005) Prospective Recruitment of Patients with Congestive Heart Failure using an Ad-hoc Binary Classifier. Journal of Biomedical Informatics 2005;38(2):145-153. Abstract
  6. Pakhomov, S., Schonwetter, M., Bachenko, J. (2001). Generating Training Data for Medical Dictations. Proceedings of the 2nd Meeting of the North American Chapter of the Association for Computational Linguistics 2001; 1-8. Abstract
  7. Pakhomov, SV, Hanson, P., Bjornsen, S., Smith, SA. (2008). Automatic classification of foot examination findings using clinical notes and machine learning. J Am Med Inform Assoc. 2008 Mar-Apr;15(2):198-202. Abstract
  8. Pakhomov SV, Buntrock JD, Chute CG. (2006). Automating the assignment of diagnosis codes to patient encounters using example-based and machine learning techniques. J Am Med Inform Assoc. 2006 Sep-Oct;13(5):516-25. Abstract