Back to search

Article

The Inefficacy of Artificial Intelligence Large Language Models in Healthcare: A Clinical and Statistical Perspective

2026-03-27

Abstract excerpt

<h4>Objective: </h4> This perspective piece examines the role of Large Language Models (LLMs) in healthcare, arguing that despite significant investment, these models have had only a limited impact. Moreover, we argue that LLMs must replicate key phases of primary healthcare delivery to be a force multiplier, a necessary condition to address the global burden of disease. <h4>Discussion:</h4> We argue that LLMs lac...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
960ff113-ecc9-5cd0-9833-3a971f62280b
DOI
10.20944/preprints202603.2228.v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
The Inefficacy of Artificial Intelligence Large Language Models in Healthcare: A Clinical and Statistical PerspectiveDOI 10.20944/preprints202603.2228.v1
Select a neighboring publication to make it the new centre.