AIMC Topic: Skin Neoplasms

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Explainable deep learning approaches for high precision early melanoma detection using dermoscopic images.

Scientific reports Jul 8, 2025
Detecting skin melanoma in the early stage using dermoscopic images presents a complex challenge due to the inherent variability in images. Utilizing dermatology datasets, the study aimed to develop Automated Diagnostic Systems for early skin cancer ...
Deep Learning Image Processing, Computer-Assisted Early Detection of Cancer Dermoscopy Reproducibility of Results Image Interpretation, Computer-Assisted Melanoma Skin Neoplasms Humans
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Machine learning to detect melanoma exploiting nuclei morphology and Spatial organization.

Scientific reports Jul 1, 2025
Cutaneous melanoma is one of the most lethal forms of skin cancer, and its incidence is increasing globally. Its diagnosis typically relies on manual histopathological examination, a process that is both complex and time consuming. In this study, we ...
Machine Learning Melanoma Image Processing, Computer-Assisted Cell Nucleus Skin Neoplasms Humans
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Automatic melanoma detection using an optimized five-stream convolutional neural network.

Scientific reports Jul 1, 2025
Melanoma is among the deadliest forms of malignant skin cancer, with the number of cases increasing dramatically worldwide. Its early and accurate diagnosis is crucial for effective treatment. However, automatic melanoma detection has several signifi...
Algorithms Melanoma Skin Neoplasms Humans Neural Networks, Computer Convolutional Neural Networks Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Dermoscopy Deep Learning
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Design of Block-Scrambling-Based privacy protection mechanism in healthcare using fusion of transfer learning models with Hippopotamus optimization algorithm.

Scientific reports Jul 1, 2025
In the human body, the skin is the main organ. Nearly 30-70% of individuals globally have skin-related health issues, for whom efficient and effective analysis is essential. A general method dermatologists use for analyzing skin illnesses is dermosco...
Diagnosis, Computer-Assisted Computer Security Algorithms Skin Neoplasms Dermoscopy Humans Machine Learning
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Urgency vs triage prioritisation: appropriateness of referrer-rated urgency of referrals to a public dermatology service.

The New Zealand medical journal Jun 27, 2025
AIM: To characterise the appropriateness of community referrer-rated urgency among dermatology referrals.
Young Adult Adult Middle Aged Adolescent Male Melanoma Skin Neoplasms Aged Humans Referral and Consultation Female Dermatology Triage Child, Preschool New Zealand Child Skin Diseases
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Enhancing and advancements in deep learning for melanoma detection: A comprehensive review.

Computers in biology and medicine Jun 7, 2025
Melanoma, although not the most common skin cancer, poses a significant global health challenge, particularly in Europe, where incidence rates are high. Traditional melanoma diagnosis through biopsies can be invasive, but advancements in artificial i...
Skin Neoplasms Deep Learning Image Interpretation, Computer-Assisted Humans Melanoma
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Skin cancer segmentation and classification by implementing a hybrid FrCN-(U-NeT) technique with machine learning.

PloS one Jun 2, 2025
Skin cancer is a severe and rapidly advancing condition that can be impacted by multiple factors, including alcohol and tobacco use, allergies, infections, physical activity, exposure to UV light, viral infections, and the effects of climate change. ...
Skin Neoplasms Image Processing, Computer-Assisted Machine Learning Humans Algorithms Neural Networks, Computer Melanoma
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Generating dermatopathology reports from gigapixel whole slide images with HistoGPT.

Nature communications May 27, 2025
Histopathology is the reference standard for diagnosing the presence and nature of many diseases, including cancer. However, analyzing tissue samples under a microscope and summarizing the findings in a comprehensive pathology report is time-consumin...
Image Processing, Computer-Assisted Humans Artificial Intelligence Natural Language Processing Skin Neoplasms Dermatology
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Mobile applications for skin cancer detection are vulnerable to physical camera-based adversarial attacks.

Scientific reports May 24, 2025
Skin cancer is one of the most prevalent malignant tumors, and early detection is crucial for patient prognosis, leading to the development of mobile applications as screening tools. Recent advances in deep neural networks (DNNs) have accelerated the...
Computer Security Photography Neural Networks, Computer Skin Neoplasms Melanoma Humans Mobile Applications
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Updated Techniques for Melanoma Diagnosis.

Dermatologic clinics May 12, 2025
Melanoma, an aggressive skin cancer, requires timely diagnostics for improved patient outcomes. The ABCDE criteria-assessing asymmetry, borders, color, diameter, and evolution-serve as foundational guidelines for early detection. Non-invasive tools l...
Early Detection of Cancer Photography Skin Neoplasms Dermoscopy Humans Algorithms Artificial Intelligence Melanoma
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