Evaluating large language models for simplifying non-English medical consent with clinician involvement

Nature·Apr 1

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Researchers are exploring the use of large language models to simplify medical consent and other healthcare-related documents for non-english speakers, with some studies focusing on specific applications such as genetic testing, brain MRI reports, and discharge summaries. The models are being evaluated for their safety, efficacy, and ability to preserve patient privacy. Various studies are investigating the potential of these models in different areas of healthcare, including cardiology and mental health care.

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Evaluating GPT-4’s ability to generate informed consent material for genetic testing

Nature·Nov 3

Safety and efficacy of privacy-preserving models to create Lay summaries of brain MRI reports

Nature·Jan 27

A comprehensive qualitative analysis of patient dialogue summarization using large language models applied to noisy, informal, non-English real-world data

Nature·Aug 27

Operationalizing machine-assisted translation in healthcare

Nature·Sep 30

Evaluation of a large language model to simplify discharge summaries and provide cardiological lifestyle recommendations

Nature·May 29

Automated generation of discharge summaries: leveraging large language models with clinical data

Nature·May 12

A scoping review of large language models for generative tasks in mental health care | npj Digital Medicine

Nature·Apr 30

The use of large language models in detecting Chinese ultrasound report errors | npj Digital Medicine

Nature·Jan 28

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