• Skip to primary navigation
  • Skip to main content
  • Skip to footer
Stanford Aging and Ethnogeriatrics Research Center (SAGE Center)

Stanford Aging and Ethnogeriatrics Research Center (SAGE Center)

Ace Aging

  • LinkedIn
  • Twitter
  • Home
  • About Us
  • Awardees
  • Faculty
  • Research Methodology Podcasts
  • Research
  • Contact Us

Fall 2020 NIH Virtual Seminar

Registration for the National Institutes of Health Regional Meeting is open and free of charge! The virtual seminar will be from Tuesday October 27-20. This is a great opportunity to learn about new funding opportunities (i.e., current areas of special interest or concern to the NIH), interpretation of NIH policy, and demystify the application and review process. Registration closes October 9, but please sign up ASAP in case there is a cap on the number of registrants. 

Registration Link: https://nihvirtualseminar2020.vfairs.com/en/registration 

Below I have highlighted a few sessions I think would be particularly useful for early career researchers: 

  • Keynote with Dr. Michael Lauer
  • Navigating NIH Programs to Advance Your Career
  • Rigor and Reproducibility: Back to Basics
  • Let’s Look At Peer Review
  • NIH Peer Review: “Live” Mock Study Section
  • An Overview of NIH Policies on Human Subjects Research
  • Including Diverse Populations in NIH-funded Clinical Research

If you’re more familiar with the basics of NIH, the “Open Mike with Dr. Michael Lauer” session is usually quite good. For an hour, Dr. Lauer will answer any questions posed by the audience. 

Another great opportunity is the “Ask the Experts”. In the past, this session involved signing up and meeting 1:1 with NIH program officers, scientific review officers, and grants policy experts. It appears that NIH will hold some version of this at the virtual seminar, so keep an eye out for how to sign up for these. 

Share this:

  • Twitter
  • Facebook

Ace Aging

Footer

Stanford Medicine

  • About
  • School Administration
  • Contact
  • Maps & Directions
  • Jobs

 

  • Basic Science Departments
  • Clinical Science Departments
  • Academic Programs
  • Diversity Programs

Healthcare

  • Find a physician
  • Clinical Trials
  • Patient Information
  • Contact

Related

  • Ethnogeriatrics
  • Salud (Spanish Health Site)
  • Project Respect
  •   Find People
  •   Visit Stanford
  •   Search Clinical Trials
  •   Give a Gift

Copyright © 2023 Stanford Medicine
Privacy Policy | Terms of Use

    Next-Generation Artificial Intelligence for Diagnosis: From Predicting Diagnostic Labels to "Wayfinding"

    Julia Adler-Milstein, PhD1; Jonathan H. Chen, MD, PhD; Gurpreet Dhaliwal, MD

    Improving the diagnostic process is a quality and safety priority.With the digitization of health records and rapid expansion of health data, the cognitive demand on the diagnostician has increased. The use of artificial intelligence (AI) to assist human cognition has the potential to reduce this demand and associated diagnostic errors. However, current AI tools have not realized this potential, due in part to the long-standing focus of these tools on predicting final diagnostic labels instead of helping clinicians navigate the dynamic refinement process of diagnosis. This Viewpoint highlights the importance of shifting the role of diagnostic AI from predicting labels to “wayfinding” (interpreting context and providing cues that guide the diagnostician).