AINS graduate specialization

Healthcare AI specialization

Three courses · reference 9 credits in a 36-credit stack

The Healthcare AI track prepares cohorts to apply machine learning and NLP in regulated clinical-adjacent contexts: imaging pipelines, cohort analytics, and human–AI collaboration in decision support. Courses emphasize measurement discipline, fairness awareness, and realistic deployment constraints—not practicing medicine.

Partners license all three courses as a concentration students complete after core AI foundations, or pilot a subset aligned with local accreditors and clinical partners.

In the reference graduate layout, this cluster occupies nine specialization credits toward a ~36-credit degree; your registrar defines official titles, prerequisites, and stack rules.

What institutions get

  • Evaluate imaging and population-health models with clinically plausible protocols (education / simulation).
  • Communicate limitations, bias risks, and governance hooks for CDS-style tools.
  • Package artifacts institutions can map to graduate certificates or degree concentrations.

Courses in this cluster

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