Location

Phoenix, Arizona

Contact

Patel.Bhavik@mayo.edu

SUMMARY

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.

Focus areas

  • 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.

Professional highlights

  • Director of Artificial Intelligence, 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

PROFESSIONAL DETAILS

Primary Appointment

  1. Senior Associate Consultant, Department of Radiology

Academic Rank

  1. Associate Professor of Radiology

EDUCATION

  1. MBA Anderson School of Management, University of California Los Angeles
  2. Fellow - Abdominal Imaging; NIH/NCI Fellow in Stanford Cancer Imaging Stanford Hospitals & Clinics
  3. Chief Resident - Diagnostic Radiology University of Alabama Medical Center
  4. Residency - Diagnostic Radiology University of Alabama Medical Center
  5. Residency - General Surgery Brigham and Women's Hospital, Harvard Medical School
  6. MD - Medicine University of Alabama School of Medicine
  7. BS - Microbiology University of Alabama

Clinical Studies

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Publications

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