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    Jejo Koola

    TitleAssistant Clinical Professor
    SchoolUniversity of California, San Diego
    Address9500 Gilman Drive #0881
    CA La Jolla 92093
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      Collapse Biography 
      Collapse Education and Training
      Vanderbilt University, Nashville, TNBiomedical Informatics
      Department of Veterans Affairs, Nashville, TN09/2016Fellowship in Biomedical Informatics
      Medical College of Virginia, Richmond, VAMedicine06/2011Internal Medicine Residency
      Medical Univ. of South Carolina, Charleston, SCMD05/2008Medicine
      Purdue University, West Lafayette, INBiology, Computer Science

      Collapse Overview 
      Collapse Overview
      Dr. Jejo Koola joined UCSD faculty in 2017. He received his MD degree from the Medical University of South Carolina and subsequently completed his residency in Internal Medicine at the Medical College of Virginia in Richmond, Virginia in 2011. Following residency, Dr. Koola completed a post-doctoral fellowship in Biomedical Informatics through the Department of Veterans Affairs in conjunction with Vanderbilt University.

      Dr. Koola has a joint appointment in Hospital Medicine and Biomedical Informatics. His research interests are in using machine learning to build predictive models utilizing very large observational cohort data. He applies models to improving the care of multi-morbid patients, particularly patients with advanced liver disease.

      Collapse Research 
      Collapse Research Activities and Funding
      Assessing efficacy of passive and active forms of expressive art therapy in inpatient services
      University of California San Diego Health Sciences Academic Senate GrantJun 1, 2017 - May 31, 2018
      Role: Co-Investigator
      Automated Surveillance and Intervention among Patients with Liver Cirrhosis
      Department of Veterans Affairs HSR&D IIR 13-052Jun 1, 2014 - Jun 1, 2018
      Role: Co-Investigator

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      Collapse Bibliographic 
      Collapse Publications
      Publications listed below are automatically derived from MEDLINE/PubMed and other sources, which might result in incorrect or missing publications. Researchers can login to make corrections and additions, or contact us for help.
      List All   |   Timeline
      1. Koola J, Cao A, Perkins A, Chen G, Ho SB, Matheny ME. Hepatology. Post-Discharge Mortality in a National Cohort of Veterans Affairs Patients with Cirrhosis. 2016; S1(64):862A.
      2. Herbsman T, Forster L, Molnar C, Dougherty R, Christie D, Koola J, Ramsey D, Morgan PS, Bohning DE, George MS, Nahas Z. Motor threshold in transcranial magnetic stimulation: the impact of white matter fiber orientation and skull-to-cortex distance. Hum Brain Mapp. 2009 Jul; 30(7):2044-55. PMID: 18973261; PMCID: PMC2893589.
      3. Nahas Z, Teneback C, Chae JH, Mu Q, Molnar C, Kozel FA, Walker J, Anderson B, Koola J, Kose S, Lomarev M, Bohning DE, George MS. Serial vagus nerve stimulation functional MRI in treatment-resistant depression. Neuropsychopharmacology. 2007 Aug; 32(8):1649-60. PMID: 17203016.
        View in: PubMed
      4. Hajcak G, Molnar C, George MS, Bolger K, Koola J, Nahas Z. Emotion facilitates action: a transcranial magnetic stimulation study of motor cortex excitability during picture viewing. Psychophysiology. 2007 Jan; 44(1):91-7. PMID: 17241144.
        View in: PubMed
      5. Borckardt JJ, Nahas Z, Koola J, George MS. Estimating resting motor thresholds in transcranial magnetic stimulation research and practice: a computer simulation evaluation of best methods. J ECT. 2006 Sep; 22(3):169-75. PMID: 16957531.
        View in: PubMed
      6. Mu Q, Nahas Z, Johnson KA, Yamanaka K, Mishory A, Koola J, Hill S, Horner MD, Bohning DE, George MS. Decreased cortical response to verbal working memory following sleep deprivation. Sleep. 2005 Jan; 28(1):55-67. PMID: 15700721.
        View in: PubMed
      7. Mishory A, Molnar C, Koola J, Li X, Kozel FA, Myrick H, Stroud Z, Nahas Z, George MS. The maximum-likelihood strategy for determining transcranial magnetic stimulation motor threshold, using parameter estimation by sequential testing is faster than conventional methods with similar precision. J ECT. 2004 Sep; 20(3):160-5. PMID: 15343000.
        View in: PubMed
      8. Koola J, Ho SB, Matheny ME. An Electronic Health Record Phenotyping Algorithm for Identifying Patients with Hepatorenal Syndrome.