Dr. Hakan Ay is an MD with residency training in Neurology and fellowship training in Vascular Neurology. He currently serves as an Associate Professor at Harvard Medical School with appointments in both departments of Neurology and Radiology at the Massachusetts General Hospital. Dr. Ay has 28 years of experience in patient care and research in basic and clinical neuroscience in academia. He is productive scholar with several high-impact scientific publications. He has served as a PI or co-PI in industry-sponsored and NIH-funded studies. Dr. Ay is an active member of American Heart Association where he serves as a member of the Stroke Council. He is a seasoned teacher committed to teaching and supporting student, residents, and fellows to succeed in their careers.
Dr Ay’s main research focus has been on developing automated decision-support systems for stroke. His systems extract the information in neuroimaging that is not visible to the human eye, harmonize it with clinical and laboratory information from a patient’s diagnostic work-up, and provide an output that enhances precision in diagnosis, risk stratification, and prognostication after acute stroke. Dr. Ay has a proven skillset to overcome the technical hurdles that prevents such technologies from being deployed, from generating well-curated discovery and validation datasets to guiding physicists and computer scientists in developing new machine learning tools.
Dr. Ay’s research program also focuses on identifying the brain’s intrinsic neuroprotective and anti-inflammatory circuits leveraged by external neurostimulation using advanced imaging techniques in experimental animals as well as in humans. His work has demonstrated that non-invasive vagus nerve stimulation can offer potential for treatment of stroke.
Lastly, Dr. Ay is a strong advocate of interdisciplinary collaboration and actively work with the faculty from other departments to integrate translational research into clinical practice. Dr. Ay runs a research program that brings vascular neurologists, internists, and radiologists together to explore the effects of brain injury such as stroke on internal organ systems such as the heart, lungs, and the immune system.
1. Ay H, Furie KL, Singhal A, Smith WS, Sorensen AG, Koroshetz WJ. An evidence based causative classification system for acute ischemic stroke. Ann Neurol 2005; 58(5):688-97.
2. Ay H, Koroshetz WJ, Benner T, Vangel MG, Wu O, Schwamm LH, et al. Transient ischemic attack with infarction: a unique syndrome? Ann Neurol 2005;57(5):679-86.
3. Ay H, Koroshetz WJ, Benner T, Vangel MG, Melinosky C, Arsava EM, et al. Neuroanatomic Correlates of Stroke-Related Myocardial Injury. Neurology 2006;66:1325-1329.
4. Ay I, Nasser R, Simon B, Ay H. Transcutaneous Cervical Vagus Nerve Stimulation Ameliorates Acute Ischemic Injury in Rats. Brain Stimul. 2016;9(2):166-73.
5. Arsava EM, Kim G-M, Oliveria-Filho J, Gungor L, Noh HJ, Lordelo MJ, et al. Prediction of early recurrence after acute ischemic stroke. JAMA Neurol. 2016;73:396-401
Causative Classification of Ischemic Stroke (CCS) System: This is a web-based, automated system licensed by the MGH that identifies the most likely cause of stroke based on clinical, laboratory, and imaging data available from typical stroke work-up.
Clinical and Imaging Based Prediction of Stroke Risk after TIA (CIP System): This is a web based automated system to estimate the 7-day risk of stroke after a TIA based on clinical and imaging characteristics of TIA.
Recurrence Risk Estimator-90 (RRE-90): This is a web-based automated system to estimate the 90-day risk of stroke after an ischemic stroke.