Carnegie Mellon University

Transforming Health Care With Machine Learning

Machine Learning algorithms can process vast amounts of information and spot patterns, hallmarks of diagnosing patients and identifying risk factors.

Tepper School faculty are using machine learning methods to develop early diagnostic tools for cancer, Alzheimer's disease, and cardiac disease; treat sleep apnea; estimate surgery duration; and connect health care providers and patients using digital platforms.

Faculty Experts

Ben Moseley

Benjamin Moseley, Assistant Professor of Operations Research, Carnegie Bosch Junior Faculty Chair

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Research Interests

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Andrew Li, Assistant Professor of Operations Research

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Research Interests

  • Personalized medicine: Applies optimization, statistics, and machine learning tools to developing diagnostic and predictive tests for early-stage cancer, Alzheimer's, and cardiac disease.

Courses

  • 47-841 Applications of High-Dimensional Statistics

Tim Derdenger

Tim Derdenger, Associate Professor of Marketing and Strategy

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Research Interests

  • Internet of Things and Artificial Intelligence Platforms: Development and scaling of new digital platforms through strategic sales arrangements.

Courses

  • Executive Education custom programs with health care firms.

Will Kaigler

Will Kaigler, Assistant Teaching Professor of Entrepreneurship

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Research Interests

  • Obstructive Sleep Apnea: Use of machine learning and computer vision in treating obstructive sleep apnea.

Entrepreneurship

  • medSage Technologies LLC (2002): Sold to Philips Electronics in 2010.
  • NewCare Solutions LLC (2011).

Courses

  • 45-906 The Business of Health Care Innovation
  • Executive Education: Innovation in Health Care

Consulting

  • Curavi Health
  • Apollo Neuro
  • Root Health
  • Carigogo
  • BehAlvior
  • PHRQL
  • AlphaLab