Stanford
University
  • Stanford Home
  • Maps & Directions
  • Search Stanford
  • Emergency Info
  • Terms of Use
  • Privacy
  • Copyright
  • Trademarks
  • Non-Discrimination
  • Accessibility
© Stanford University.  Stanford, California 94305.
Artificial Intelligence in Healthcare: The Hope, The Hype, The Promise, The Peril | Stanford HAI

Stay Up To Date

Get the latest news, advances in research, policy work, and education program updates from HAI in your inbox weekly.

Sign Up For Latest News

Skip to content
  • About

    • About
    • People
    • Get Involved with HAI
    • Support HAI
    • Subscribe to Email
  • Research

    • Research
    • Fellowship Programs
    • Grants
    • Student Affinity Groups
    • Centers & Labs
    • Research Publications
    • Research Partners
  • Education

    • Education
    • Executive and Professional Education
    • Government and Policymakers
    • K-12
    • Stanford Students
  • Policy

    • Policy
    • Policy Publications
    • Policymaker Education
    • Student Opportunities
  • AI Index

    • AI Index
    • AI Index Report
    • Global Vibrancy Tool
    • People
  • News
  • Events
  • Industry
  • Centers & Labs
Navigate
  • About
  • Events
  • AI Glossary
  • Careers
  • Search
Participate
  • Get Involved
  • Support HAI
  • Contact Us
Your browser does not support the video tag.
event

Artificial Intelligence in Healthcare: The Hope, The Hype, The Promise, The Peril

Status
Past
Date
Friday, November 08, 2019 8:00 AM - 5:00 PM PST/PDT
Topics
Healthcare

This conference is anchored and building on the release of the Special National Academy of Medicine (NAM) publication titled: “Artificial Intelligence in Healthcare: The Hope, The Hype, The Promise, The Peril.” Co-led by Michael Matheny and Sonoo Thadaney Israni.

Objectives At the conclusion of this activity, participants should be able to: 

  1. Evaluate AI in the healthcare landscape

  2. Critically assess the opportunities for AI in healthcare

  3. Develop appropriate criteria for evaluating/deploying AI solutions

  4. Build frameworks for creating and testing AI healthcare solutions

Share
Link copied to clipboard!

Related Events

NVIDIA & Marlowe: Scaling Data Science Workloads with RAPIDS
WorkshopJul 15, 20262:00 PM - 3:30 PM
July
15
2026

This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!

Event

NVIDIA & Marlowe: Scaling Data Science Workloads with RAPIDS

Jul 15, 20262:00 PM - 3:30 PM

This workshop will cover how NVIDIA RAPIDS offers a seamless experience to enable GPU-acceleration for many existing data science tasks with zero code changes. You will learn how to use GPU-accelerated tools to conduct data science faster, leading to more scalable, reliable, and cost-effective results!

Empirical Methods in the Age of AI Conference
ConferenceOct 02, 2026
October
02
2026

Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.

Event

Empirical Methods in the Age of AI Conference

Oct 02, 2026

Save the Date. Artificial intelligence is transforming how researchers collect, analyze, and learn from data. As AI systems become increasingly integrated into scientific discovery, business decision-making, and policy analysis, they are reshaping both the questions researchers can ask and the methods they use to answer them.

This conference is anchored and building on the release of the Special National Academy of Medicine (NAM) publication titled: “Artificial Intelligence in Healthcare: The Hope, The Hype, The Promise, The Peril.” Co-led by Michael Matheny and Sonoo Thadaney Israni.

Objectives 

At the conclusion of this activity, participants should be able to:

  1. Evaluate AI in the healthcare landscape

  2. Critically assess the opportunities for AI in healthcare

  3. Develop appropriate criteria for evaluating/deploying AI solutions

  4. Build frameworks for creating and testing AI healthcare solutions