Work

Bridging the mentorship divide: how large language models could reshape medical workforce equity

Year: 2026

Type: article

Abstract: Mentorship in predictive large language models (LLMs) presents both opportunities and risks of inequity if these systems are not designed with care. Mentorship quietly shapes medical careers, yet opportunities for it remain unequal. LLMs can analyze student writing and may reveal potential that exams overlook. This predictive capacity could inform fairer mentorship and direct support to students who need it most, helping build a more equitable medical workforce.

Source: npj Digital Medicine

DOI: 10.1038/s41746-025-02167-z

Authors: Nghia Phu Nguyen, Phillip Tran

Institution: Nam Can Tho University

Language: English

Topic: Artificial Intelligence in Healthcare and Education

Subfield: Health Informatics

Field: Medicine

Domain: Health Sciences

SDGs: Reduced inequalities, Quality education

Open Access status: gold

Estimated APC paid: $4,090