AIMC Topic: Melanoma

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GraphMHC: Neoantigen prediction model applying the graph neural network to molecular structure.

PloS one Mar 27, 2024
Neoantigens are tumor-derived peptides and are biomarkers that can predict prognosis related to immune checkpoint inhibition by estimating their binding to major histocompatibility complex (MHC) proteins. Although deep neural networks have been prima...
Antigens, Neoplasm Melanoma Humans Molecular Structure Peptides Neural Networks, Computer
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Optimizing time prediction and error classification in early melanoma detection using a hybrid RCNN-LSTM model.

Microscopy research and technique Mar 22, 2024
Skin cancer is a terrifying disorder that affects all individuals. Due to the significant increase in the rate of melanoma skin cancer, early detection of skin cancer is now more critical than ever before. Malignant melanoma is one of the most seriou...
Early Detection of Cancer Skin Melanoma, Cutaneous Malignant Humans Deep Learning Neural Networks, Computer Image Processing, Computer-Assisted Melanoma Skin Neoplasms Algorithms
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Enhancing skin lesion classification with advanced deep learning ensemble models: a path towards accurate medical diagnostics.

Current problems in cancer Mar 13, 2024
Skin cancer, including the highly lethal malignant melanoma, poses a significant global health challenge with a rising incidence rate. Early detection plays a pivotal role in improving survival rates. This study aims to develop an advanced deep learn...
Melanoma Humans Skin Neoplasms Neural Networks, Computer Deep Learning
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Combining artificial intelligence and human expertise for more accurate dermoscopic melanoma diagnosis: A 2-session retrospective reader study.

Journal of the American Academy of Dermatology Feb 29, 2024
Clinical Competence Artificial Intelligence Retrospective Studies Humans Skin Neoplasms Melanoma Dermoscopy
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Patient and dermatologists' perspectives on augmented intelligence for melanoma screening: A prospective study.

Journal of the European Academy of Dermatology and Venereology : JEADV Feb 27, 2024
BACKGROUND: Artificial intelligence (AI) shows promising potential to enhance human decision-making as synergistic augmented intelligence (AuI), but requires critical evaluation for skin cancer screening in a real-world setting.
Cohort Studies Early Detection of Cancer Dermatologists Middle Aged Attitude of Health Personnel Photography Melanoma Skin Neoplasms Adult Male Aged Artificial Intelligence Prospective Studies Female Humans
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Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in skin cutaneous melanoma.

Melanoma research Feb 16, 2024
Intratumor heterogeneity (ITH) is defined as differences in molecular and phenotypic profiles between different tumor cells and immune cells within a tumor. ITH was involved in the cancer progression, aggressiveness, therapy resistance and cancer rec...
Machine Learning Prognosis Female Humans Male Immunotherapy Melanoma, Cutaneous Malignant Melanoma Skin Neoplasms
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Fusion between an Algorithm Based on the Characterization of Melanocytic Lesions' Asymmetry with an Ensemble of Convolutional Neural Networks for Melanoma Detection.

The Journal of investigative dermatology Jan 29, 2024
Melanoma is still a major health problem worldwide. Early diagnosis is the first step toward reducing its mortality, but it remains a challenge even for experienced dermatologists. Although computer-aided systems have been developed to help diagnosis...
Dermoscopy Sensitivity and Specificity Diagnosis, Computer-Assisted Melanoma Skin Neoplasms Nevus Nevus, Pigmented Neural Networks, Computer Early Detection of Cancer Algorithms Diagnosis, Differential Humans
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Can ChatGPT vision diagnose melanoma? An exploratory diagnostic accuracy study.

Journal of the American Academy of Dermatology Jan 19, 2024
Humans Artificial Intelligence Melanoma
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Evaluating deep learning-based melanoma classification using immunohistochemistry and routine histology: A three center study.

PloS one Jan 19, 2024
Pathologists routinely use immunohistochemical (IHC)-stained tissue slides against MelanA in addition to hematoxylin and eosin (H&E)-stained slides to improve their accuracy in diagnosing melanomas. The use of diagnostic Deep Learning (DL)-based supp...
ROC Curve Immunohistochemistry MART-1 Antigen Humans Melanoma Deep Learning
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Using multiple real-world dermoscopic photographs of one lesion improves melanoma classification via deep learning.

Journal of the American Academy of Dermatology Jan 8, 2024
Humans Algorithms Dermoscopy Melanoma Deep Learning Skin Neoplasms
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