Development of a Transfer Learning-Based, Multimodal Neural Network for Identifying Malignant Dermatological Lesions From Smartphone Images

A transfer learning-based, multimodal neural network can accurately identify malignant skin lesions from smartphone images and clinical data. External validation with larger, more diverse datasets is needed to assess the model's generalisability and support clinical adoption.

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Publication Details

Journal
Cancer Informatics
Published
2025-06-24
DOI
https://doi.org/10.1177/11769351251349891
Citations
1
Primary Topic
Cutaneous Melanoma Detection and Management
Type
article
Field-Weighted Citation Impact
1.05
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article

Development of a Transfer Learning-Based, Multimodal Neural Network for Identifying Malignant Dermatological Lesions From Smartphone Images

Jiawen Deng, Kaden Venugopal, Eddie Guo, Heather Jianbo Zhao et al.
1 citations
Cancer Informatics
Cutaneous Melanoma Detection and Management
1.05
article

Development of a Transfer Learning-Based, Multimodal Neural Network for Identifying Malignant Dermatological Lesions From Smartphone Images

Jiawen Deng, Kaden Venugopal, Eddie Guo, Heather Jianbo Zhao, Myron Moskalyk
article en
1 citations

Abstract

A transfer learning-based, multimodal neural network can accurately identify malignant skin lesions from smartphone images and clinical data. External validation with larger, more diverse datasets is needed to assess the model's generalisability and support clinical adoption.

Cancer InformaticsVol. 24
University of Ottawa (CA), University of Calgary (CA), University of Toronto (CA), Queen's University (CA), Public Health Ontario (CA)
Openalex Percentile: Top 21%
Cutaneous Melanoma Detection and Management
1.05
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Development of a Transfer Learning-Based, Multimodal Neural Network for Identifying Malignant Dermatological Lesions From Smartphone Images — Jiawen Deng, Kaden Venugopal, et al. · Cancer Informatics (2025) | TGRS Research Map | TGRS