AIMC Topic: Skin Neoplasms

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Editorial: New Target for Skin Cancer.

Experimental dermatology
Skin cancer encompasses a diverse spectrum of malignancies with increasing global incidence and persistent clinical challenges. Despite advances in therapies such as immune checkpoint inhibitors and targeted agents, many patients-especially those wit...

Improving skin lesion classification through saliency-guided loss functions.

Computers in biology and medicine
Deep learning has significantly advanced computer-aided diagnosis, particularly in skin lesion classification. However, achieving high classification performance and providing explainable model predictions remain challenging in medical imaging. To ta...

Self-supervised multi-modality learning for multi-label skin lesion classification.

Computer methods and programs in biomedicine
BACKGROUND: The clinical diagnosis of skin lesions involves the analysis of dermoscopic and clinical modalities. Dermoscopic images provide detailed views of surface structures, while clinical images offer complementary macroscopic information. Clini...

Skin Cancer Detection Using Deep Learning Approaches.

Cancer biotherapy & radiopharmaceuticals
This review examined multiple deep learning (DL) methods, including artificial neural networks (ANNs), convolutional neural networks (CNNs), k-nearest neighbors (KNNs), as well as generative adversarial networks (GANs), relying on their abilities to...

Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study.

Nature communications
Artificial intelligence (AI) systems substantially improve dermatologists' diagnostic accuracy for melanoma, with explainable AI (XAI) systems further enhancing their confidence and trust in AI-driven decisions. Despite these advancements, there rema...

A cost-effective approach using generative AI and gamification to enhance biomedical treatment and real-time biosensor monitoring.

Scientific reports
Biosensors are crucial to the diagnosis process since they are designed to detect a specific biological analyte by changing from a biological entity into electrical signals that can be processed for further inspection and analysis. The method provide...

Patient research priorities in melanoma: a national qualitative interview study.

The British journal of dermatology
BACKGROUND: Outcomes for advanced melanoma have improved following the advent of immunotherapy and targeted therapy. This heralds a need for reconsideration of future research agendas. Patients can - and are keen to - help identify and prioritize res...

Enhancing basal cell carcinoma classification in preoperative biopsies via transfer learning with weakly supervised graph transformers.

BMC medical imaging
BACKGROUND: Basal cell carcinoma (BCC) is the most common skin cancer, placing a significant burden on healthcare systems globally. Developing high-precision automated diagnostics requires large annotated datasets, which are costly and difficult to o...

Towards Skin Cancer Detection Through Low Resolution Images.

Studies in health technology and informatics
Currently, dermatologists need to check numerous image reports (high resolution) for diagnosing skin conditions, and Machine Learning (ML) models can help with this tedious task. However, current ML models usually work best with high-quality images i...

Exploring Differential Diagnosis-Based Explainable AI: A Case Study in Melanoma Detection.

Studies in health technology and informatics
Melanoma is a significant global health concern, with rising incidence rates and high mortality when diagnosed late. Artificial Intelligence (AI) models, especially models using deep learning techniques, have shown promising results in melanoma detec...