Deep learning in assisting dermatologists in classifying basal cell carcinoma from seborrheic keratosis

The deep learning model demonstrated significant potential in aiding dermatologists in classifying BCC from SK.

Authors

Institutions

Publication Details

Journal
Frontiers in Oncology
Published
2025-04-24
DOI
https://doi.org/10.3389/fonc.2025.1507322
Citations
2
Primary Topic
Cutaneous Melanoma Detection and Management
Type
article
Field-Weighted Citation Impact
2.09
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deep learning in assisting dermatologists in classifying basal cell carcinoma from seborrheic keratosis

Xuan-Guang Ye, Yang Gao, Jing Li, Lihong Mei et al.
2 citations
Frontiers in Oncology
Cutaneous Melanoma Detection and Management
2.09
article

Deep learning in assisting dermatologists in classifying basal cell carcinoma from seborrheic keratosis

Xuan-Guang Ye, Yang Gao, Jing Li, Lihong Mei, Mengyao Cao, Xiangdong Liu
article en
2 citations

Abstract

The deep learning model demonstrated significant potential in aiding dermatologists in classifying BCC from SK.

Frontiers in OncologyVol. 15
Jinshan Hospital of Fudan University (CN), Shanghai Eighth People Hospital (CN), Shanghai Sixth People's Hospital (CN)
Openalex Percentile: Top 13%
Cutaneous Melanoma Detection and Management
2.09
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.