Comment on Korkmaz et al. A Deep Learning and Explainable AI-Based Approach for the Classification of Discomycetes Species. Biology 2025, 14, 719

Authors

Institutions

Publication Details

Journal
Biology
Published
2026-01-06
DOI
https://doi.org/10.3390/biology15020106
Citations
1
Primary Topic
AI in cancer detection
Type
article
Field-Weighted Citation Impact
52.10
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Comment on Korkmaz et al. A Deep Learning and Explainable AI-Based Approach for the Classification of Discomycetes Species. Biology 2025, 14, 719

Emmanuel Pio Pastore
1 citations
Biology
AI in cancer detection
52.10
article

Comment on Korkmaz et al. A Deep Learning and Explainable AI-Based Approach for the Classification of Discomycetes Species. Biology 2025, 14, 719

Emmanuel Pio Pastore
article en
1 citations

Abstract

No abstract available for this paper.
BiologyVol. 15(2)
University of Calabria (IT)
Openalex Percentile: Top 1%
AI in cancer detection
52.10
DOIOpen Access PDFOpenAlex
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.

Comment on Korkmaz et al. A Deep Learning and Explainable AI-Based Approach for the Classification of Discomycetes Species. Biology 2025, 14, 719 — Emmanuel Pio Pastore · Biology (2026) | TGRS Research Map | TGRS