AIMC Topic: Melanoma

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Advancing dermoscopy through a synthetic hair benchmark dataset and deep learning-based hair removal.

Journal of biomedical optics Nov 19, 2024
SIGNIFICANCE: Early detection of melanoma is crucial for improving patient outcomes, and dermoscopy is a critical tool for this purpose. However, hair presence in dermoscopic images can obscure important features, complicating the diagnostic process....
Image Interpretation, Computer-Assisted Hair Hair Removal Dermoscopy Deep Learning Image Processing, Computer-Assisted Neural Networks, Computer Melanoma Skin Neoplasms Humans
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Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images.

Sensors (Basel, Switzerland) Nov 12, 2024
Skin cancer is the most common type of cancer in the United States and is estimated to affect one in five Americans. Recent advances have demonstrated strong performance on skin cancer detection, as exemplified by state of the art performance in the ...
Melanoma Skin Neoplasms Humans Deep Learning ROC Curve Neural Networks, Computer Image Processing, Computer-Assisted Algorithms Skin
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The established of a machine learning model for predicting the efficacy of adjuvant interferon alpha1b in patients with advanced melanoma.

Frontiers in immunology Nov 12, 2024
BACKGROUND: Interferon-alpha1b (IFN-α1b) has shown remarkable therapeutic potential as adjuvant therapy for melanoma. This study aimed to develop five machine learning models to evaluate the efficacy of postoperative IFN-α1b in patients with advanced...
Adult Female Male Melanoma Middle Aged Neoplasm Staging Interferon-alpha Aged Adjuvants, Immunologic Humans Chemotherapy, Adjuvant ROC Curve Machine Learning Treatment Outcome Retrospective Studies
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Transforming Skin Cancer Diagnosis: A Deep Learning Approach with the Ham10000 Dataset.

Cancer investigation Nov 10, 2024
Skin cancer (SC) is one of the three most common cancers worldwide. Melanoma has the deadliest potential to spread to other parts of the body among all SCs. For SC treatments to be effective, early detection is essential. The high degree of similarit...
Deep Learning Skin Neoplasms Carcinoma, Basal Cell Humans Melanoma
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Machine Learning-enhanced Signature of Metastasis-related T Cell Marker Genes for Predicting Overall Survival in Malignant Melanoma.

Journal of immunotherapy (Hagerstown, Md. : 1997) Nov 7, 2024
In this study, we aimed to investigate disparities in the tumor immune microenvironment (TME) between primary and metastatic malignant melanoma (MM) using single-cell RNA sequencing (scRNA- seq ) and to identify metastasis-related T cell marker genes...
Prognosis Female Melanoma Humans Machine Learning Male Gene Expression Profiling Nomograms Neoplasm Metastasis Tumor Microenvironment Biomarkers, Tumor T-Lymphocytes
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Enhanced convolutional neural network architecture optimized by improved chameleon swarm algorithm for melanoma detection using dermatological images.

Scientific reports Nov 6, 2024
Early detection and treatment of skin cancer are important for patient recovery and survival. Dermoscopy images can help clinicians for timely identification of cancer, but manual diagnosis is time-consuming, costly, and prone to human error. To cond...
Melanoma Deep Learning Image Processing, Computer-Assisted Humans Skin Neoplasms Early Detection of Cancer Neural Networks, Computer Dermoscopy Algorithms
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Deep Learning With Optical Coherence Tomography for Melanoma Identification and Risk Prediction.

Journal of biophotonics Oct 27, 2024
Malignant melanoma is the most severe skin cancer with a rising incidence rate. Several noninvasive image techniques and computer-aided diagnosis systems have been developed to help find melanoma in its early stages. However, most previous research u...
Melanoma Deep Learning Image Processing, Computer-Assisted Mice Tomography, Optical Coherence Skin Neoplasms Animals Risk Assessment
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Personalized melanoma grading system: a presentation of a patient with four melanomas detected over two decades with evolving whole-body imaging and artificial intelligence systems.

Dermatology online journal Oct 15, 2024
Melanoma is a life-threatening tumor that significantly impacts individuals' health and society worldwide. Therefore, its diagnostic tools must be revolutionized, representing the most remarkable human efforts toward successful management. This retro...
Retrospective Studies Melanoma Skin Neoplasms Male Neoplasm Grading Dermoscopy Aged Humans Artificial Intelligence Genetic Testing Photography Whole Body Imaging
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Integrating color histogram analysis and convolutional neural networks for skin lesion classification.

Computers in biology and medicine Oct 12, 2024
The color of skin lesions is a crucial diagnostic feature for identifying malignant melanoma and other skin diseases. Typical colors associated with melanocytic lesions include tan, brown, black, red, white, and blue-gray. This study introduces a nov...
Color Skin Image Interpretation, Computer-Assisted Melanoma Skin Neoplasms Dermoscopy Algorithms Databases, Factual Humans Neural Networks, Computer
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Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma.

Frontiers in immunology Sep 17, 2024
BACKGROUND: Immunotherapy has revolutionized skin cutaneous melanoma treatment, but response variability due to tumor heterogeneity necessitates robust biomarkers for predicting immunotherapy response.
Machine Learning Treatment Outcome Mice Prognosis Immunotherapy Skin Neoplasms Humans Animals Melanoma Gene Expression Regulation, Neoplastic Transcriptome Tumor Microenvironment Gene Expression Profiling Gene Regulatory Networks Biomarkers, Tumor
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