Jason Yeates Adams, M.D., M.S.
Co-Chair, UC Davis Health Data Oversight Committee (HDOC)
Co-Director, UC Davis Health Data Provisioning Core (DPC)
Director of Data and Analytics Strategy, UC Davis Health
Associate Professor
To see if Jason Yeates Adams is accepting new patients, or for assistance finding a UC Davis doctor, please call 800-2-UCDAVIS (800-282-3284).
Locations and Contact
UC Davis Medical Group - Sacramento (J Street)
Pulmonary, Critical Care and Sleep Medicine
2825 J St.
Sacramento, CA 95816
Phone: 916-734-8230
Fax: 916-734-4582
Additional Numbers
Physician Referrals
Philosophy of Care
Patients come to UC Davis Health to get the best care possible, have access to the latest medical research, and be cared for by doctors that know how to educate. As a physician and scientist at UC Davis Health, I strive to provide exceptional care, informed by the latest medical advancements, and explained in a way that everyone can understand. I work collaboratively with patients and their families to get the diagnosis right and develop a patient-centered plan of care with the same high standards I would expect for the care of my own loved ones.
Clinical Interests
Dr. Adams is a Pulmonary and Critical Care Medicine physician with extensive clinical experience caring for patients with critical illness and both acute and chronic pulmonary diseases. He has special interests in cardiovascular critical care and in the management of patients with respiratory failure requiring mechanical ventilation. He also sees patients in the general Pulmonary Medicine clinics.
Research/Academic Interests
Dr. Adams’s research is focused on the use of artificial intelligence (AI) methods, physiologic sensors, and electronic health record data to improve the way we diagnose critical illnesses and predict clinical trajectories in the intensive care. His research lab is multidisciplinary with co-investigators and graduate students from Computer Science, Engineering, Biomedical Informatics, Pulmonary and Critical Care Medicine, Nursing, and Respiratory Therapy. Dr. Adams welcomes students with a passion for applying data science methods to the challenges facing patients in the intensive care unit.
Division
Pulmonary, Critical Care, and Sleep Medicine
Center/Program Affiliation
Undergraduate School
B.A., UC Santa Barbara, Santa Barbara CA 1998
Medical School
M.D., UC San Francisco, San Francisco CA 2006
Other School
M.S., Health Informatics, UC Davis, Davis CA 2014
Internship
Internal Medicine, Stanford University Hospitals & Clinics, Stanford CA 2006-2007
Residency
Internal Medicine, Stanford University Hospitals and Clinics, Stanford CA 2007-2009
Fellowship
Howard Hughes Medical Institute Scholar, Howard Hughes Medical Institute/UC San Francisco, San Francisco CA 2004-2005
Fellowship
ACGME Fellow, Division of Pulmonary, Critical Care, and Sleep Medicine, UC Davis Medical Center, Sacramento CA 2009-2012
See https://pubmed.ncbi.nlm.nih.gov/?term=adams+jy&sort=date&size=200 for additional publications.
Rehm GB, Cortés-Puch I, Kuhn BT, Nguyen J, Fazio SA, Johnson MA, Anderson NR, Chuah CN, Adams JY. Use of Machine Learning to Screen for Acute Respiratory Distress Syndrome Using Raw Ventilator Waveform Data. Crit Care Explor. 2021 Jan 8;3(1):e0313. doi:10.1097/CCE.0000000000000313. PMID:33458681.
Rehm GB, Woo SH, Chen XL, Kuhn BT, Cortes-Puch I, Anderson NR, Adams JY, Chuah CN. Leveraging IoTs and Machine Learning for Patient Diagnosis and Ventilation Management in the Intensive Care Unit. IEEE Pervasive Comput. 2020 Jul-Sep;19(3):68-78. doi:10.1109/mprv.2020.2986767. Epub 2020 May 25. PMID:32754005.
Fazio S, Doroy A, Da Marto N, Taylor S, Anderson N, Young HM, Adams JY. Quantifying Mobility in the ICU: Comparison of Electronic Health Record Documentation and Accelerometer-Based Sensors to Clinician-Annotated Video. Crit Care Explor. 2020 Apr 29;2(4):e0091. doi:10.1097/CCE.0000000000000091. PMID:32426733.
Rehm GB, Kuhn BT, Nguyen J, Anderson NR, Chuah CN, Adams JY. Improving Mechanical Ventilator Clinical Decision Support Systems with a Machine Learning Classifier for Determining Ventilator Mode. Stud Health Technol Inform. 2019 Aug 21;264:318-322. doi:10.3233/SHTI190235. PMID:31437937.
Rehm GB, Kuhn BT, Nguyen J, Anderson NR, Chuah CN, Adams JY. Improving Mechanical Ventilator Clinical Decision Support Systems with a Machine Learning Classifier for Determining Ventilator Mode. Stud Health Technol Inform. 2019 Aug 21;264:318-322. doi:10.3233/SHTI190235. PMID:31437937.
Adams JY, Lieng MK, Kuhn BT, Rehm GB, Guo EC, Taylor SL, Delplanque JP, Anderson NR. Development and Validation of a Multi-Algorithm Analytic Platform to Detect Off-Target Mechanical Ventilation. Sci Rep. 2017 Nov 3;7(1):14980. doi:10.1038/s41598-017-15052-x. PMID:29101346.