Abstract: The incidence of skin cancer, particularly melanoma, has been on the rise globally, presenting significant challenges in diagnosis and treatment due to limitations in traditional methods, ...
Deep learning based melanoma detection system using a custom CNN architecture. Includes model comparison, class imbalance handling, and a Gradio web interface for real-time skin lesion prediction.
Obstetrics & Gynecology Hospital of Fudan University, Shanghai Key Lab of Reproduction and Development, Shanghai Key Lab of Female Reproductive Endocrine Related Diseases, Shanghai, China Background: ...
Scientists have uncovered how too much sunlight can flip a hidden switch inside skin cells that makes inflammation spiral out of control and increases the risk of cancer. Their research reveals that ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Individual prediction uncertainty is a key aspect of clinical prediction model performance; however ...
A machine learning project to predict loan default risk using financial and credit history data. Built as part of a team capstone project in master degree at Deakin University. BayesCOOP is a scalable ...
Please provide your email address to receive an email when new articles are posted on . Patients are increasingly using AI to diagnose their dermatologic conditions and triage malignant lesions.
Melanoma remains one of the hardest skin cancers to diagnose because it often mimics harmless moles or lesions. While most artificial intelligence (AI) tools rely on dermoscopic images alone, they ...
Enhanced prediction capability: Machine learning-based system matches and in some cases outperforms traditional forecasting systems, with particular improvements in northern Europe where conventional ...
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