A new AI automatic model for the histopathologic diagnoses of melanoma and nevi

Authors

Federico Venturi (ORCID: https://orcid.org/0000-0001-5053-4172)
Emi Dika (ORCID: https://orcid.org/0000-0003-3186-2861)
Nico Curti (ORCID: https://orcid.org/0000-0001-5802-1195)
Aldo Gardini (ORCID: https://orcid.org/0000-0002-2164-5815)
Giulia Veronesi (ORCID: https://orcid.org/0000-0001-9228-6082)

Institutions

Azienda USL di Bologna (IT)
University of Bologna (IT)

Publication Details

Journal: EJC Skin Cancer
Published: 2025-01-01
DOI: https://doi.org/10.1016/j.ejcskn.2025.100471
Primary Topic: AI in cancer detection
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

A new AI automatic model for the histopathologic diagnoses of melanoma and nevi

Federico Venturi, Emi Dika, Nico Curti, Aldo Gardini et al.

Jan 1, 2025

EJC Skin Cancer

AI in cancer detection

article

A new AI automatic model for the histopathologic diagnoses of melanoma and nevi

Federico Venturi, Emi Dika, Nico Curti, Aldo Gardini, Giulia Veronesi

January 1, 2025article en

Abstract

No abstract available for this paper.

EJC Skin CancerVol. 3

Azienda USL di Bologna (IT), University of Bologna (IT)

Openalex Percentile: Top 97%

AI in cancer detection

DOI Open Access PDF OpenAlex

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.

A new AI automatic model for the histopathologic diagnoses of melanoma and nevi — Federico Venturi, Emi Dika, et al. · EJC Skin Cancer (2025) | TGRS Research Map | TGRS