Professor Oguz Akbilgic

He is a health informaticist with expertise in AI and statistical methodology and their applications in healthcare. His health informatics areas of application include risk prediction, detection and monitoring of cardiovascular disease, adverse maternal events and movement disorders. He has extensive experience in integrating AI models with wearable devices that can remotely collect physiological waveform data, especially, electrocardiogram. His work has been funded by both federal agencies and private organizations such as Michael J Fox Foundation. He is the PI of two active R01 and one R21 as well as contributing to many other federally funded research studies. He is also an innovator and entrepreneur aiming to translate AI models into Software as Medical Devices that can help improving health outcomes through clinical implementations. His efforts led to an FDA Breakthrough Designation for an AI model that can track cardiac biomarkers, non-invasively and remotely via weaerables.