Work

Leveraging GPT-4o for Automated Extraction of Neural Projections from Scientific Literature.

Year: 2025

Type: article

Abstract: Sudden Unexpected Death in Epilepsy (SUDEP) is a major cause of death for epilepsy patients having uncontrolled seizures. Understanding the complex neural circuits within the central nervous system is crucial for understanding the mechanisms underlying cardiorespiratory regulation, particularly in the context of SUDEP. This study explores the potential of GPT-4o, a cutting-edge language model, to automate the extraction of neural projections from scientific literature. We developed prompts to extract neuroscientific structures, extract projections, and perform synonym harmonization. Applying the approach to four neuroscientific articles, the method extracted 205 projections. A random sample of 100 projections identified was handed over to a domain expert for review where 95 were found to be correct. Therefore, GPT-4o was determined to be accurate in parsing complex scientific texts in extracting neural projections. Future work will involve extracting additional entities like techniques and species information for the projections identified.

Source: PubMed

Authors: Rashmie Abeysinghe, Gorbachev Jowah, Licong Cui, Samden D Lhatoo, Guo-Qiang Zhang

Institution: The University of Texas Health Science Center at Houston

Language: English

Topic: Biomedical Text Mining and Ontologies

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: green

Funders: National Institutes of Health, National Institute of Neurological Disorders and Stroke

Awards: Engagement and outreach to achieve a FAIR data ecosystem for the BICAN, An informatics framework for SUDEP Risk Marker Identification and Risk Assessment, SCH: Neurophysiological AI-Ready Data Resource

OpenAlex ID: W4411256846

FWCI:

Cites: 23

Cited by:

Related to: 10