AIMC Topic: Skin Neoplasms

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Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification.

PloS one
Skin cancer is considered globally as the most fatal disease. Most likely all the patients who received wrong diagnosis and low-quality treatment die early. Though if it is detected in the early stages the patient has fairly good chance and the afore...

Diagnosis and prognosis of melanoma from dermoscopy images using machine learning and deep learning: a systematic literature review.

BMC cancer
BACKGROUND: Melanoma is a highly aggressive skin cancer, where early and accurate diagnosis is crucial to improve patient outcomes. Dermoscopy, a non-invasive imaging technique, aids in melanoma detection but can be limited by subjective interpretati...

Boosting skin cancer diagnosis accuracy with ensemble approach.

Scientific reports
Skin cancer is common and deadly, hence a correct diagnosis at an early age is essential. Effective therapy depends on precise classification of the several skin cancer forms, each with special traits. Because dermoscopy and other sophisticated imagi...

Multi-scale feature fusion of deep convolutional neural networks on cancerous tumor detection and classification using biomedical images.

Scientific reports
In the present scenario, cancerous tumours are common in humans due to major changes in nearby environments. Skin cancer is a considerable disease detected among people. This cancer is the uncontrolled evolution of atypical skin cells. It occurs when...

Melanoma Breslow Thickness Classification Using Ensemble-Based Knowledge Distillation With Semi-Supervised Convolutional Neural Networks.

IEEE journal of biomedical and health informatics
Melanoma is considered a global public health challenge and is responsible for more than 90% deaths related to skin cancer. Although the diagnosis of early melanoma is the main goal of dermoscopy, the discrimination between dermoscopic images of in s...

Attention-Guided Learning With Feature Reconstruction for Skin Lesion Diagnosis Using Clinical and Ultrasound Images.

IEEE transactions on medical imaging
Skin lesion is one of the most common diseases, and most categories are highly similar in morphology and appearance. Deep learning models effectively reduce the variability between classes and within classes, and improve diagnostic accuracy. However,...

HistoColAi: An open-source web platform for collaborative digital histology image annotation with AI-driven predictive integration.

Computer methods and programs in biomedicine
Digital pathology is now a standard component of the pathology workflow, offering numerous benefits such as high-detail whole slide images and the capability for immediate case sharing between hospitals. Recent advances in deep learning-based methods...

Fluorescence images of skin lesions and automated diagnosis using convolutional neural networks.

Photodiagnosis and photodynamic therapy
In recent years, interest in applying deep learning (DL) to medical diagnosis has rapidly increased, driven primarily by the development of Convolutional Neural Networks and Transformers. Despite advancements in DL, the automated diagnosis of skin ca...