The Clinical Utility of AI-Based Prediction and Stratification Models

This article outlines a strategy of pursuing “prediction without hype” and judging AI by whether it is trustworthy, transportable, and useful at the point of care.

Authors

David R. Goldsmith (ORCID: https://orcid.org/0000-0002-4002-175X)
Paris Alexandros Lalousis (ORCID: https://orcid.org/0000-0001-9642-3080)
Raquel Iniesta (ORCID: https://orcid.org/0000-0003-1153-5417)

Institutions

Emory University (US)
King's College London (GB)

Publication Details

Journal: JAMA Psychiatry
Published: 2026-11-04
DOI: https://doi.org/10.1001/jamapsychiatry.2026.3579
Primary Topic: Artificial Intelligence in Healthcare and Education
Type: article
Field-Weighted Citation Impact: 0.00

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article

The Clinical Utility of AI-Based Prediction and Stratification Models

David R. Goldsmith, Paris Alexandros Lalousis, Raquel Iniesta

Nov 4, 2026

JAMA Psychiatry

Artificial Intelligence in Healthcare and Education

article

The Clinical Utility of AI-Based Prediction and Stratification Models

David R. Goldsmith, Paris Alexandros Lalousis, Raquel Iniesta

November 4, 2026article en

Abstract

This article outlines a strategy of pursuing “prediction without hype” and judging AI by whether it is trustworthy, transportable, and useful at the point of care.

JAMA Psychiatry

Emory University (US), King's College London (GB)

Openalex Percentile: Top 22%

Artificial Intelligence in Healthcare and Education

DOI Source OpenAlex

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The Clinical Utility of AI-Based Prediction and Stratification Models — David R. Goldsmith, Paris Alexandros Lalousis, et al. · JAMA Psychiatry (2026) | TGRS Research Map | TGRS