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Stanford Aging and Ethnogeriatrics Research Center (SAGE Center)

Stanford Aging and Ethnogeriatrics Research Center (SAGE Center)

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LEARN

Welcome to the Longevity, Equity, and Aging, Research Network (LEARN).
LEARN is a multi-institutional research consortium, supporting transdisciplinary, multi-level research on longevity, equity, aging and ethnogeriatrics.

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Discover the latest innovations and current projects in aging

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Clarifying key research methodology issues

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Stanford Researchers Named to Clinical Research Forum Top Ten List

Dr. James Zou, Lead of the SAGE Center Methods Core, receives the Clinical Research Forum 2022 Top Ten Clinical Research Achievement Award in recognition of his study, “Evaluating eligibility criteria of oncology trials using real-world data and AI,” the results of which were published in Nature last year. Dr. Zou was presented the award at the 2022 Translational Science Conference in Chicago, IL in April, 2022.

Junior Investigator Accomplishments:
Research projects solving pressing problems in aging
2022 David H. Solomon Award for Clinical Research and Leadership in Aging

Dr. VJ Periyakoil is the recipient of the  2022 David H. Solomon Memorial Award, a special award given in honor of the beloved Founding Director of the UCLA Multicampus Program in Geriatric Medicine and Gerontology (MPGMG) for nationally recognized leadership in geriatric medicine. This is the highest award given by UCLA to a clinical research leader in the field of aging.

LEARN Awardees

Click on the profiles to read their biography.

Ivan Mejia-Guevara, PhD
Fatima Rodriguez, MD, Mph
Carolyn Rodriguez, MD, PhD
Alesha Heath, PhD
Kevin Alexander, MD
Suzanne Tamang, PhD
Kacie Deters, PhD

Róbert Pálovics, PhD

Travis Shivley-Scott, PhD

Juan Banda, PhD
Jonathan H. Chen, MD, PhD
Monroe D. Kennedy III, PhD
Morteza Noshad, PhD
Nazish Sayed, MD, PhD
Jiajun Wu, PhD
Xin Zhou, PhD
Shoa Clarke, MD, PhD
Ngan Huang, PhD
Gen Shinozaki, MD

Ace Aging

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    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).