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

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.

Authors

Institutions

Publication Details

Journal
PubMed
Published
2025-01-01
Primary Topic
Time Series Analysis and Forecasting
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Licong Cui, Rashmie Abeysinghe, Samden Lhatoo, Guo‐Qiang Zhang et al.
PubMed
Time Series Analysis and Forecasting
article

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

Licong Cui, Rashmie Abeysinghe, Samden Lhatoo, Guo‐Qiang Zhang, Gorbachev Jowah
article en

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.

PubMedVol. 2025
The University of Texas Health Science Center at Houston (US)
Openalex Percentile: Top 85%
Time Series Analysis and Forecasting
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Leveraging GPT-4o for Automated Extraction of Neural Projections from Scientific Literature. — Licong Cui, Rashmie Abeysinghe, et al. · PubMed (2025) | TGRS Research Map | TGRS