Andrew Beam.

Andrew Beam, PhD, Program Director

Medical professionals using digital technology

Innovating to Provide Patient-centric Care

  • Module 1: The History and Foundations of AI

    AI has come a long way in a short amount of time. Examine its evolution, differentiate between supervised and self-supervised learning and explore emerging AI applications in health care.

  • Module 2: A Framework for the AI Development Pipeline

    Creating and implementing an AI health care solution involves a careful balance of training, validation and deployment. Explore each stage of the AI development pipeline and formulate an idea for an AI-driven health care solution that you will work on throughout the program to fulfill the capstone requirement.

  • Module 3: From the Lab to the Real World

    Leveraging the power of AI in a health care setting can be challenging. Examine the complexities of developing successful AI-driven products for the health care industry and identify the factors that must be considered to create a successful product.

  • Module 4: Transparency, Reproducibility and Generalizability in AI

    Risk prediction models assess the likelihood of a given outcome. Discover common evaluation measures used with these models and the level of certainty required for clinical decision-making.

  • Module 5: The Potential for Bias and Harm in AI

    The AI development pipeline offers a host of benefits, but it also introduces potential ethical concerns. Examine each pipeline stage through the lens of ethics and equip yourself with the knowledge to identify and avoid ethically problematic choices and practices throughout the development process.

  • Module 6: AI for Startups

    AI implementation carries a unique set of considerations for startups. Guided by a leader in the AI startup world, learn to transform your idea for an AI-first health care solution into a compelling story and viable investor pitch.

  • Module 7: AI for Wearable Data

    Person-generated health data (PGHD) gathered by wearable devices and machine learning algorithms offer a wide range of new health care possibilities. Explore the advantages and disadvantages of leveraging machine learning to collect and assess wearable data and examine the role of community benchmarks and transparency in developing machine learning methods.

  • Module 8: Live Session—Capstone Presentations

    A viable pitch is instrumental to securing funding for an AI-first health care solution. Join the members of your cohort as some of them share pitches for their solutions and examine what makes an effective pitch and why.

Teaching Team