Jacob Krive, PhD, MBA, FAMIA

Dr. Jacob Krive maintains parallel industry and academic careers focused on biomedical informatics, healthcare data science and machine learning, population health, and cognitive engineering. His research passions span such areas as clinical and multi-specialty analytics, patient data management, oncology survivorship analytics, artificial intelligence, medical ontologies, economics of health informatics and AI, healthcare project management innovation, master patient data management, and biomedical informatics curriculum design. Dr. Krive has extensive healthcare industry experience and held multiple people and technology leadership roles with large organizations such as Endeavor Health, Advocate Health Care, IBM, Healthcare Services Corporation, among several others. Dr. Krive received his BS, MS, and MBA degrees from University of Maryland University College, and PhD from Nova Southeastern University. He is a Fellow of the American Medical Informatics Association (FAMIA) and also holds CPHIMS, Lean Six Sigma, and Epic Cogito Project Manager professional certifications. Dr. Krive designed several courses for BHIS graduate programs, co-founded Healthcare Data Science track of the MS program, co-designed innovative elective AI course for College of Medicine students, founded cardio-oncology AI research lab, teaches and oversees student research, publishes, and presents his funded work internationally. Dr. Krive is a member of the Editorial Board of the JMIR Online Journal of Public Health Informatics and an Associate Editor of Computational and Structural Biotechnology Journal. He peer-reviews for many global conferences and impactful journals.

Seba, F., Isola, M., Mills, L., Zalake, M., & Krive, J. (2025). Incorporating Generative AI Into a Health Informatics Curriculum to Build 21st Century Competencies: Multisite Pre-Post Study. JMIR Medical Informatics, 13:e76507. https://medinform.jmir.org/2025/1/e76507

Adesanya, O., Ebengho, I., Ogbeide, O., Abusin, S., Guha, A., Krive, J., & Okwuosa, T. (2025). Artificial Intelligence (AI) Models Effectively Detect Cancer Therapy-Related Cardiac Dysfunction (CTRCD): a Diagnostic Test Accuracy (DTA) Meta-Analysis. Circulation, 152(Suppl_3), A4365007-A4365007.

Ross, J., Schnell, R., Krive, J., Dalgetty, A., & Parker, T. (2025). The BRAIN Book. Altona, MB, Canada: Friesens Books.

Khera, R., Asnani, A. H., Krive, J., Addison, D., Zhu, H., Vasbinder, A., Fleming, M. R., Arnaut, R., Razavi, P., & Okwuosa, T. M. (2025). Artificial Intelligence to Enhance Precision Medicine in Cardio-Oncology: A Scientific Statement From the American Heart Association. Circulation: Genomic and Precision Medicine, e000097.

Krive, J., & Chertok, D. (2024). Advancing cardiovascular disease prediction machine learning models with psychological factors. Journal of the American College of Cardiology (JACC): Advances, 3(9 Part II), https://www.sciencedirect.com/science/article/pii/S2772963X24004162

Krive, J., Isola, M., Chang, L.F., Patel, T.N., Anderson, M., & Sreedhar, R. (2023). Grounded in reality: Artificial intelligence in medical education. Journal of the American Medical Informatics (JAMIA) Open, 6(2). https://academic.oup.com/jamiaopen/article/6/2/ooad037/7188283

Gniadek, T.J., Kang, J., Theparee, T., & Krive, J. (2023). Framework for classifying explainable artificial intelligence (XAI) algorithms in clinical medicine. JMIR Online Journal of Public Health Informatics, 5:e50934. https://ojphi.jmir.org/2023/1/e50934

Al-Droubi, S.S., Jahangir, E., Kochendorfer, K.M., Krive, M., Laufer-Perl, M., Gilon, D., Okwuosa, T.M., Gans, C.P., Arnold, J.H., Bhaskar, S.T., Yasin, H.A., & Krive, J. (2023). Artificial intelligence modeling to assess the risk of cardiovascular disease in oncology patients. European Heart Journal – Digital Health, 4(3), https://academic.oup.com/ehjdh/advance-article/doi/10.1093/ehjdh/ztad031/7156811?searchresult=1

Isola, M., & Krive, J. (2022). Innovation of health data science curricula. Journal of the American Medical Informatics (JAMIA) Open, 5(3), https://academic.oup.com/jamiaopen/article/5/3/ooac073/6678087?guestAccessKey=0b3bcbcc-b979-4c08-8c45-03fdb4698a1a

Konchak, C.W., Krive, J., Au, L., Chertok, D., Dugad, P., Granchalek, G., Livschiz, E., Mandala, R., McElvania, E., Park, C., Robicsek, A., Sabatini, L.M., Shah, N.S., Kaul, K. (2021). From testing to decision making: A data-driven analytics COVID-19 response. Academic Pathology, 8, https://journals.sagepub.com/doi/full/10.1177/23742895211010257

Dr. Krive serves on the editorial board in the Associate Editor role with Computational & Structural Biotechnology Journal and JMIR Online Journal of Public Health Informatics. He is peer reviewer for JACC, Nature, AMIA, European Heart Journal, Health Informatics Journal, JMIR Medical Education, AME Medical Journal, HIMSS, IJSISE, HCA, CRC Press, and other journals, conferences, and publishers. He was a Guest Editor for the Digital Twins special issue published in 2025-2026 by the Computational & Structural Biotechnology Journal.

PhD, Information Systems, Nova Southeastern University, 2013
MS, Management Information Systems, University of Maryland University College, 2006
MBA, University of Maryland University College, 2005
BS, Computer Studies and Management Studies, University of Maryland University College, 2002

Certified Professional in Healthcare Information Management and Systems (CPHIMS) certification from Healthcare Information Management and Systems Society (HIMSS)

Lean Six Sigma Green Belt certification from Purdue University

Cogito Project Manager (CPM) certification from Epic Systems

Basic Certificate in Quality from Institute for Healthcare Improvement

AMIA

IEEE

HIMSS

Krive, J. (2026). In search of technology soul: Seeking productive value of AI in medicine. UIC Journal Club for Clinical Informatics Fellows, UIC Hospital & College of Medicine, Chicago, Illinois, United States of America.

Krive, J. (2026). Delivering real patient care with AI. The Biomedical Engineering AI Collective. University of Illinois at Chicago, https://luma.com/fxhlwqa8.

Krive, J. (2026). Digital twins in medicine. UIC Journal Club for Clinical Informatics Fellows, UIC Hospital & College of Medicine, Chicago, Illinois, United States of America.

Krive, J. (2026). Discovering clinical value of AI: Medical subspecialty and cardio-oncology analytics. Informatics Power Talk Lecture. University of Alabama School of Medicine, Birmingham, AL.

Seba, F., Isola, M., Mills, L., Zalake, M., & Krive, J. (2025). Embedding generative AI into health informatics education and assessing learning outcomes. Annual Symposium of the American Medical Informatics Association (AMIA), Atlanta, GA, United States of America, https://amia.org/education-events/amia-2025-annual-symposium

Al-Droubi, S.S., Wilcox, A., Foraker, R., Johnson, J., & Krive, J. (2025). Designing machine learning algorithms and analytics to support interdisciplinary clinical subspecialties. Annual Symposium of the American Medical Informatics Association (AMIA), Atlanta, GA, United States of America, https://amia.org/education-events/amia-2025-annual-symposium

Krive, J. (2025). Augmented intelligence for advancing humanity: Neurology and beyond. BRAIN Conference, Raynolds Alberta Museum, Wetaskiwin, Alberta, Canada.

Mills, L., Krive, J., Seba, F., Zalake, M., & Krive, J. (2025). Empowering students with generative artificial intelligence (AI): A case- and competency-based approach to health informatics education. Commission on Accreditation for Health Informatics and Information Management Education (CAHIIM) Summit, Chicago, Illinois, United States of America, https://www.cahiim.org/resources/events/cahiim-2025-summit-on-higher-education/.

Adesanya, O., Ebengho, I., Guha, A., Abusin, S., Ogbeide, O., Krive, J., & Okwuosa, T. (2025). Artificial intelligence (AI) models effectively detect cancer therapy-related cardiac dysfunction (CTRCD): A diagnostic test accuracy (DTA) meta-analysis. American Heart Association’s Scientific Sessions 2025, New Orleans, Louisiana, United States of America, https://professional.heart.org/en/meetings/scientific-sessions/

Krive, J. (2025). Augmented intelligence in medicine: A more humane and purposeful AI concept. International Council on Systems Engineering (INCOSE), Schaumburg, Illinois, United States of America, https://www.incose.org.

Krive, J. (2024). AI opportunities in healthcare: Hype vs. value and innovation. International Council on Systems Engineering (INCOSE), Schaumburg, Illinois, United States of America, https://www.incose.org.

Al-Droubi, S.S., Wilcox, A., Foraker, R., & Krive, J. (2024). Designing machine learning algorithms and analytics to support interdisciplinary clinical subspecialties. Annual Symposium of the American Medical Informatics Association (AMIA), San Francisco, CA, United States of America, https://amia.org/education-events/amia-2024-annual-symposium

Krive, J. (2024). Artificial intelligence for neurology: A breakthrough or just a new automation tool? BRAIN Conference, University of Alberta, Camrose, Canada.

Krive, J., McCabe, K., & Karnik, N. (2024). Artificial intelligence and the social determinants of health panel. 12^th Annual Diversity, Inclusion, and Health Equity Symposium, Chicago, Illinois, United States of America, https://www.chisite.org/events-all/healthequity2024

Imas, P., & Krive, J. (May 2024). Organizational culture shift towards self-service analytics via SlicerDicer. Epic Experts Group Meeting (XGM) conference, Madison, WI, United States of America, https://xgm.epic.com

Balogun, S., & Krive, J. (2024). Real world evidence of cardiotoxicity: Breast cancer oncology regimens. Summit of the American Medical Informatics Association (AMIA), Boston, MA, United States of America, https://amia.org/education-events/amia-2024-informatics-summit.

Isola, M., Zalake, M., Mills, L., Krive, J. (2023). Impact of generative AI on health informatics education. Proceedings of the Linking Informatics and Education Academic Forum (LIEAF) at the Annual Symposium of the American Medical Informatics Association (AMIA), New Orleans, LA, United States of America, https://amia.org/education-events/amia-2023-annual-symposium/lieaf

Al-Droubi, S.S., Bhaskar, S.T., Jahangir, E., Schaffer, K., Kochendorfer, K.M., Krive, M., Laufer-Perl, M., Gilon, D., Okwuosa, T.M., Gans, C.P., Arnold, J.H., & Krive, J. (2023). Implementation of EHR based cardio oncology algorithm for generating patient referrals in community practice. Proceedings of the Annual Symposium of the American Medical Informatics Association (AMIA), New Orleans, LA, United States of America, https://amia.org/education-events/amia-2023-annual-symposium

Krive, J. (2023). Partnerships with oncologists to explore cardiotoxicity and partner in medical practice implementation. Annual University of Illinois Cancer Center Retreat, Chicago, Illinois, United States of America.

Krive, J. (2023). Clinical analytics and AI in support of equitable access to cardiovascular care for oncology patients. Biomedical Informatics Health Equity (BIHE) Series, University of Illinois at Chicago, Illinois, United States of America.

Krive, J. (2023). Machine learning to augment cardio-oncology medical practice operations and advance medical science. Loyola University Chicago, Parkinson School of Health Sciences and Public Health, Health Informatics Series (invited talk), Chicago, Illinois, United States of America.

Yasin, H.A., Al-Droubi, S.S., Jahangir, E., Kochendorfer, K.M., Krive, M., Laufer-Perl, M., Gilon, D., Okwuosa, T.M., Gans, C.P., Arnold, J.H., Bhaskar, S.T., Rini, B.I., & Krive, J. (2022). Artificial intelligence modelling to predict the risk of cardiotoxicity among renal cell carcinoma patients treated with vascular endothelial growth factor receptors tyrosine kinase inhibitors. International Kidney Cancer Symposium North America, Austin, Texas, United States of America, https://www.kcameetings.org/2022-ikcs-north-america.

Al-Droubi, S.S., Jahangir, E., Kochendorfer, K.M., Krive, M., Laufer-Perl, M., Gilon, D., Okwuosa, T.M., Gans, C.P., Arnold, J.H., Bhaskar, S.T., Yasin, H.A., & Krive, J. (2022). Machine learning modeling to support cardio-oncology medical practice. Annual Symposium of the American Medical Informatics Association (AMIA), Washington, DC, United States of America, https://amia.org/education-events/amia-2022-annual-symposium

Al-Droubi, S.S., Jahangir, E., Kochendorfer, K.M., Krive, M., Laufer-Perl, M., Gilon, D., Okwuosa, T.M., Gans, C.P., Arnold, J.H., Bhaskar, S.T., Yasin, H.A., Iyer, R.K., Jalali, A., Parde, N., Foulger, R., Kataria, S., Bhardwaj, C., Rodriguez Ziccardi, M., Robles Granda, M.I., McGrew, D., Chen, Y., Choundhary, A., Aouad, M., Cao, Y., Gudur, A., & Krive, J. (2022). Machine learning opportunities to support cardio-oncology research and medical practice. Applied Health Sciences (AHS) Research Day, University of Illinois at Chicago, Chicago, IL, United States of America.

Jalali, A., Huang, S., Srivastava, V., Barapatre, A., Parida, S., Kim, S., Krive, J., Kochendorfer, K. (2022). Azure modern analytics architecture for synthetic syndromic surveillance. Center for Cardiovascular Research (CCVR) Day, University of Illinois at Chicago, Chicago, IL, United States of America.

Al-Droubi, S.S., Jahangir, E., Kochendorfer, K.M., Krive, M., Laufer-Perl, M., Gilon, D., Okwuosa, T.M., Gans, C.P., Arnold, J.H., Bhaskar, S.T., Yasin, H.A., & Krive, J. (2022). Machine learning modeling to support cardio-oncology medical practice. Vanderbilt University Clinical Informatics Center Fall InformaticCon, Nashville, TN, United States of America, https://www.vumc.org/vclic/informaticcon-fall-2022  

Pauwaa, S., Akhter, N., Decara, J., Gans, C., Valencia, J., Basha, H., Pursnani, A., Kinno, M., Arif, S., Sharain, R., Chu, J., Tan, A., Krive, J., Brown, S-A., & Okwuosa., T. (2022). Opportunities and challenges for building a real world big data cohort in cardio-oncology. Illinois and Wisconsin Chapters of the American College of Cardiology, Chicago City-Wide Cardio-Oncology Clinical Conference, Rush University, Chicago, IL, United States of America.

Sreedhar, R., & Krive, J. (2022). Artificial intelligence in medical education. Introduction to Clinical Informatics Workshop, Mohamed I University (UMP). Oujda, Morocco, delivered virtually from Chicago, Illinois.

Isola, M., & Krive, J. (Sep 2022). Innovative approaches to curriculum design and preparing the health informatics workforce. Commission on Accreditation for Health Informatics and Information Management (CAHIIM) Fall Festival Summit on Higher Education. Virtual delivery from Chicago, IL, https://www.cahiim.org/event-detail/2022/09/27/default-calendar/cahiim's-fall-festival-2022-summit-on-higher-education.

Imas, P., Keaveny, O., & Krive, J. (2022). The impact of SlicerDicer self-service analytics on research innovation. Epic Expert Group Meeting (XGM) conference, Verona, WI, United States of America, https://xgm.epic.com

Krive, J., Jalali, A., Huang, S., & Kochendorfer, K. (2022). Clinical research, engineering, and AI to address wicked problems in healthcare: Cardio-oncology AI use case. Microsoft Global Broadcast on Accelerating Research in Academic Medical Centers. Recorded in Chicago, Illinois, United States of America.

Krive, J. (Jan 13, 2022). Cardio-oncology data and analytics research consortium proposal. Chicagoland Cardio-Oncology Clinical (CCC) Leadership Group, Rush University Medical Center, Chicago, IL, United States of America.

Krive, J. (2021). Artificial intelligence and analytics in support of the cardio-oncology medical practice. UIC/UIUC/Mayo Clinic workshop conducted by Illinois Discovery Partners Institute (DPI) and Center for Computational Biotechnology and Genomic Medicine (CCBGM) – an NSF Industry-University Cooperative Center. University of Illinois,  Urbana-Champaign, United States of America.

Isola, M., Sreedhar, R., Chang, L. F., Patel, T. N., Anderson, M. C., & Krive, J. (2021). Medical curriculum elective to integrate clinical analytics and artificial intelligence in preparing physicians for the digitally enabled practice. Proceedings of the Annual Symposium of the American Medical Informatics Association (AMIA), https://www.amia.org/amia2021, San Diego, CA.

Sreedhar, R., Krive, J., Isola, M., Patel, T. N., & Chang, L. F. (2021). A2IM – Artificial and augmented intelligence in medicine. 25^th Annual Meeting of the International Association of Medical Science Educators, https://julnet.swoogo.com/iamse2021. Delivered virtually from Chicago, IL – during Covid pandemic.

Imas, P., & Krive, J. (2021). Promoting research innovation and increasing productivity through SlicerDicer self-service analytics. Epic Expert Group Meeting (XGM) conference, Madison, Wisconsin, United States of America, https://xgm.epic.com. Delivered virtually from Chicago, IL – during Covid pandemic.

Gaffney, E., & Krive, J. (2021). Cogito project manager (CPM) and Cogito tools administrator (CTA) roles in legacy HIT: The story of organization-wide partnership. Epic Expert Group Meeting (XGM) conference, Madison, Wisconsin, United States of America, https://xgm.epic.com. Delivered virtually from Chicago, IL – during Covid pandemic.

Kochendorfer, K. M., Gans, C. P., Krive, M., & Krive, J. (2021). Cardio-oncology analytics. Create Wisdom Grant Workshop, University of Illinois Discovery Partners Institute & EX3 Labs. Virtual delivery from Chicago, IL – during Covid pandemic.

Chang, L. F., Krive, J., Isola, M., Patel, T. N., & Sreedhar, R. (2021). Integrating AI into medical curriculum. Winter 2021 Meeting of the Central Group on Education Affairs (CGEA) of the Association of American Medical Colleges (AAMC), https://www.aamc.org/professional-development/affinity-groups/gea/cgea. Virtual delivery from Chicago, IL – during Covid pandemic.

Krive, M., & Krive, J. (2021). Clinical analytics to support and advance cardio-oncology practice. Conference on Advancing the Cardiovascular Care of the Oncology Patient, by the American College of Cardiology (ACC), https://www.acc.org/cvoncology. Virtual delivery from Chicago, IL - during Covid pandemic.

Cardiotoxicity predictive modeling

Metabolic toxicity predictive modeling

Cancer Survivorship Working Group

Real world evidence (RWE) of oncology drugs performance in terms of cardiotoxicity in medical practice

Large language models for mental health

Professional training in machine learning for medical multi-specialties

Artificial intelligence for digital pathology

Data Commons for Long Covid tracking and clinical investigation