A Spitzoid Tumor dataset with clinical metadata and Whole Slide Images for Deep Learning models.
Journal
Scientific data
ISSN: 2052-4463
Titre abrégé: Sci Data
Pays: England
ID NLM: 101640192
Informations de publication
Date de publication:
16 10 2023
16 10 2023
Historique:
received:
27
03
2023
accepted:
22
09
2023
medline:
23
10
2023
pubmed:
17
10
2023
entrez:
16
10
2023
Statut:
epublish
Résumé
Spitzoid tumors (ST) are a group of melanocytic tumors of high diagnostic complexity. Since 1948, when Sophie Spitz first described them, the diagnostic uncertainty remains until now, especially in the intermediate category known as Spitz tumor of unknown malignant potential (STUMP) or atypical Spitz tumor. Studies developing deep learning (DL) models to diagnose melanocytic tumors using whole slide imaging (WSI) are scarce, and few used ST for analysis, excluding STUMP. To address this gap, we introduce SOPHIE: the first ST dataset with WSIs, including labels as benign, malignant, and atypical tumors, along with the clinical information of each patient. Additionally, we explain two DL models implemented as validation examples using this database.
Identifiants
pubmed: 37845235
doi: 10.1038/s41597-023-02585-2
pii: 10.1038/s41597-023-02585-2
pmc: PMC10579378
doi:
Types de publication
Dataset
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
704Subventions
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 860627
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 860627
Organisme : EC | Horizon 2020 Framework Programme (EU Framework Programme for Research and Innovation H2020)
ID : 860627
Organisme : Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness)
ID : PID2019-105142RB-C21
Organisme : Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness)
ID : PID2019-105142RB-C21
Organisme : Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness)
ID : PID2019-105142RB-C21
Organisme : Ministerio de Economía y Competitividad (Ministry of Economy and Competitiveness)
ID : PID2019-105142RB-C21
Informations de copyright
© 2023. Springer Nature Limited.
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