Hybrid deep learning models for text-based identification of gene-disease associations

Authors

Institutions

Publication Details

Journal
Bioimpacts
Published
2025-06-28
DOI
https://doi.org/10.34172/bi.31226
Citations
1
Primary Topic
Biomedical Text Mining and Ontologies
Type
article
Field-Weighted Citation Impact
0.81
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Hybrid deep learning models for text-based identification of gene-disease associations

Noor Fadhil Jumaa, Sepideh Parvizpour, Jafar Razmara, Jaber Karimpour
1 citations
Bioimpacts
Biomedical Text Mining and Ontologies
0.81
article

Hybrid deep learning models for text-based identification of gene-disease associations

Noor Fadhil Jumaa, Sepideh Parvizpour, Jafar Razmara, Jaber Karimpour
article en
1 citations

Abstract

No abstract available for this paper.
BioimpactsVol. 15
Tabriz University of Medical Sciences (IR), University of Tabriz (IR)
Openalex Percentile: Top 25%
Biomedical Text Mining and Ontologies
0.81
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.

Hybrid deep learning models for text-based identification of gene-disease associations — Noor Fadhil Jumaa, Sepideh Parvizpour, et al. · Bioimpacts (2025) | TGRS Research Map | TGRS