Can generative artificial intelligence empower target trial emulations?

The Lancet Digital Health 2026 Open access

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Authors: Zhouyu Guan, Dian Zeng, Huating Li, Tien Yin Wong, Bin Sheng
DOI: 10.1016/j.landig.2025.100950
Cited by: 8
References: 4

Abstract

Target trial emulation (TTE) is a pragmatic framework to estimate causal effects from observational data when randomised controlled trials (RCTs) are infeasible.1 While RCTs remain the gold standard for establishing causal inference between an exposure (eg, drug, device, or artificial intelligence [AI] algorithm) and a patient health outcome (eg, disease morbidity or mortality), RCTs are often constrained by high costs, long timelines, narrow eligibility criteria, ethical concerns, and limited generalisability to real-world populations.

Fields of Study & Subjects

Artificial Intelligence in Healthcare and Education Ethics in Clinical Research Meta-analysis and systematic reviews

Publication details

Journal / source
The Lancet Digital Health
Publisher
Elsevier BV
Volume
8
Issue
1
Pages
100950–100950
Publication date
1 January 2026
Language
EN