The research areas of interest for Bhavik N. Patel, M.D., M.B.A., include utilization of the latest in biomedical and computational technologies toward delivery of Artificial Intelligence (AI) enabled health care. This involves developing AI models, using traditional machine learning, natural language processing and deep learning to aid in diagnoses, future health risk prediction and therapy decision-making.
Dr. Patel focuses on developing AI models that either automate information contained within medical information, such as medical images or texts, or that extract biomarkers and features that are inherently embedded within such information but not so readily discernable by conventional methods. Through this research, collective use of the entire vast medical record for a given patient is utilized for optimal decision-making and guidance of care.
Dr. Patel also studies ways to improve the value of current medical care by developing models to affect population-level care, through incidental or opportunistic screening and risk prediction.
- AI. Dr. Patel leads a multidisciplinary team consisting of multispecialty clinicians, data scientists and computer science engineers to develop, validate and deploy AI models to augment health care providers toward improved medical decision-making.
- Operational efficiency. Work in this area relates to using developed AI models to improve the current health care delivery paradigm, either through eliminating existing bottlenecks or through new efficient utilization of existing resources.
- Value-based care delivery. Dr. Patel and his colleagues develop AI models to improve population-level outcomes through risk prediction. This involves AI models that allow opportunistic screening of future health disease onset to allow earlier intervention and preventive strategies or through model prediction of disease progression to optimally tailor current therapy.
Significance to patient care
Patients have a wealth of information captured in the electronic medical record (EMR), such as medical imaging, laboratory tests, pathology data and notes capturing the provider-patient encounter. It can be challenging to utilize the entirety of the potential predictive data that is within the EMR. Dr. Patel's research focuses on developing AI models to aid current health care providers to be able to utilize all of the aforementioned data efficiently and meaningfully toward improved patient health outcomes.
- Chief Artificial Intelligence Officer, Mayo Clinic, Phoenix, Arizona, 2023-present.
- Medical director, Artificial Intelligence and Machine Learning Enablement and Innovation, Center for Digital Health, Mayo Clinic, 2022-present.
- Director of Artificial Intelligence, Machine Intelligence in Medicine and Imaging Laboratory, Department of Radiology, Mayo Clinic, Phoenix, Arizona, 2021-present.
- Associate Editor, Artificial Intelligence section, Abdominal Radiology, 2021-present.
- Chair, Assessment Committee, Society of Advanced Body Imaging Technology, 2020-present.