AIMC Topic: Melanoma
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Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study.
Nature communications
May 21, 2025
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...
Patient research priorities in melanoma: a national qualitative interview study.
The British journal of dermatology
May 19, 2025
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...
Exploring Differential Diagnosis-Based Explainable AI: A Case Study in Melanoma Detection.
Studies in health technology and informatics
May 15, 2025
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...
Fully volumetric body composition analysis for prognostic overall survival stratification in melanoma patients.
Journal of translational medicine
May 12, 2025
BACKGROUND: Accurate assessment of expected survival in melanoma patients is crucial for treatment decisions. This study explores deep learning-based body composition analysis to predict overall survival (OS) using baseline Computed Tomography (CT) s...
NetLnc: A Network-Based Computational Framework to Identify Immune Checkpoint-Related lncRNAs for Immunotherapy Response in Melanoma.
International journal of molecular sciences
May 9, 2025
Long non-coding RNAs (lncRNAs) could alter the tumor immune microenvironment and regulate the expression of immune checkpoints (ICPs) by regulating target genes in tumors. However, only a few lncRNAs have precise functions in immunity and potential f...
Omics data classification using constitutive artificial neural network optimized with single candidate optimizer.
Network (Bristol, England)
May 1, 2025
Recent technical advancements enable omics-based biological study of molecules with very high throughput and low cost, such as genomic, proteomic, and microbionics'. To overcome this drawback, Omics Data Classification using Constitutive Artificial N...
Geometric deep learning and multiple-instance learning for 3D cell-shape profiling.
Cell systems
Mar 19, 2025
The three-dimensional (3D) morphology of cells emerges from complex cellular and environmental interactions, serving as an indicator of cell state and function. In this study, we used deep learning to discover morphology representations and understan...
Artificial intelligence in dermatopathology: a systematic review.
Clinical and experimental dermatology
Jan 27, 2025
Medical research, driven by advancing technologies like artificial intelligence (AI), is transforming healthcare. Dermatology, known for its visual nature, benefits from AI, especially in dermatopathology with digitized slides. This review explores A...
Advances in computer vision and deep learning-facilitated early detection of melanoma.
Briefings in functional genomics
Jan 15, 2025
Melanoma is characterized by its rapid progression and high mortality rates, making early and accurate detection essential for improving patient outcomes. This paper presents a comprehensive review of significant advancements in early melanoma detect...
[Research advances in the pathological diagnosis of melanocytic tumors with artificial intelligence].
Zhonghua bing li xue za zhi = Chinese journal of pathology
Jan 8, 2025
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