AIMC Topic: Skin Neoplasms

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Optimizing skin cancer screening with convolutional neural networks in smart healthcare systems.

PloS one Mar 25, 2025
Skin cancer is among the most prevalent types of malignancy all over the global and is strongly associated with the patient's prognosis and the accuracy of the initial diagnosis. Clinical examination of skin lesions is a key aspect that is important ...
Early Detection of Cancer Algorithms Delivery of Health Care Skin Neoplasms Humans Neural Networks, Computer
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Exploring the Views of Dermatologists, General Practitioners, and Melanographers on the Use of AI Tools in the Context of Good Decision-Making When Detecting Melanoma: Qualitative Interview Study.

JMIR dermatology Mar 24, 2025
BACKGROUND: Evidence that artificial intelligence (AI) may improve melanoma detection has led to calls for increased human-AI collaboration in clinical workflows. However, AI-based support may entail a wide range of specific functions for AI. To appr...
Clinical Decision-Making Female Melanoma Male Middle Aged New Zealand Skin Neoplasms Dermatologists Adult General Practitioners Humans Artificial Intelligence Australia Early Detection of Cancer Decision Making Qualitative Research Attitude of Health Personnel Interviews as Topic
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Evaluating the Diagnostic Accuracy of ChatGPT-4 Omni and ChatGPT-4 Turbo in Identifying Melanoma: Comparative Study.

JMIR dermatology Mar 21, 2025
ChatGPT is increasingly used in healthcare. Fields like dermatology and radiology could benefit from ChatGPT's ability to help clinicians diagnose skin lesions. This study evaluates the accuracy of ChatGPT in diagnosing melanoma. Our analysis indicat...
Male Humans Skin Neoplasms Middle Aged Reproducibility of Results Female Sensitivity and Specificity Melanoma
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Artificial Intelligence and Convolutional Neural Networks-Driven Detection of Micro and Macro Metastasis of Cutaneous Melanoma to the Lymph Nodes.

The American Journal of dermatopathology Mar 19, 2025
BACKGROUND: Lymph node (LN) assessment is a critical component in the staging and management of cutaneous melanoma. Traditional histopathological evaluation, supported by immunohistochemical staining, is the gold standard for detecting LN metastases....
Lymphatic Metastasis Melanoma, Cutaneous Malignant Artificial Intelligence Image Interpretation, Computer-Assisted Melanoma Skin Neoplasms Humans Convolutional Neural Networks Neural Networks, Computer Lymph Nodes
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Revealing gut microbiota biomarkers associated with melanoma immunotherapy response and key bacteria-fungi interaction relationships: evidence from metagenomics, machine learning, and SHAP methodology.

Frontiers in immunology Mar 18, 2025
INTRODUCTION: The gut microbiota is associated with the response to immunotherapy in cutaneous melanoma (CM). However, gut fungal biomarkers and bacterial-fungal interactions have yet to be determined.
Male Middle Aged Fungi Humans Bacteria Female Metagenomics Skin Neoplasms Melanoma Aged Immunotherapy Machine Learning Adult Treatment Outcome Biomarkers Gastrointestinal Microbiome
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Skin lesion segmentation with a multiscale input fusion U-Net incorporating Res2-SE and pyramid dilated convolution.

Scientific reports Mar 7, 2025
Skin lesion segmentation is crucial for identifying and diagnosing skin diseases. Accurate segmentation aids in identifying and localizing diseases, monitoring morphological changes, and extracting features for further diagnosis, especially in the ea...
Humans Neural Networks, Computer Algorithms Image Processing, Computer-Assisted Skin Skin Neoplasms Dermoscopy Skin Diseases
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A multi-stage fusion deep learning framework merging local patterns with attention-driven contextual dependencies for cancer detection.

Computers in biology and medicine Mar 6, 2025
Cancer is a severe threat to public health. Early diagnosis of disease is critical, but the lack of experts in this field, the personal assessment process, the clinical workload, and the high level of similarity in disease classes make it difficult. ...
Deep Learning Skin Neoplasms Lung Neoplasms Brain Neoplasms Neoplasms Humans Neural Networks, Computer
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Machine learning-based classification of spatially resolved diffuse reflectance and autofluorescence spectra acquired on human skin for actinic keratoses and skin carcinoma diagnostics aid.

Journal of biomedical optics Mar 4, 2025
SIGNIFICANCE: The incidence of keratinocyte carcinomas (KCs) is increasing every year, making the task of developing new methods for KC early diagnosis of utmost medical and economical importance.
Support Vector Machine Spectrometry, Fluorescence Discriminant Analysis Keratosis, Actinic Skin Optical Imaging Carcinoma, Squamous Cell Aged Aged, 80 and over Male Middle Aged Diagnosis, Computer-Assisted Machine Learning Female Skin Neoplasms Carcinoma, Basal Cell Humans
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An intelligent framework for skin cancer detection and classification using fusion of Squeeze-Excitation-DenseNet with Metaheuristic-driven ensemble deep learning models.

Scientific reports Mar 3, 2025
Skin cancer is the most dominant and critical method of cancer, which arises all over the world. Its damaging effects can range from disfigurement to major medical expenditures and even death if not analyzed and preserved timely. Conventional models ...
Humans Convolutional Neural Networks Image Processing, Computer-Assisted Algorithms Skin Neoplasms Deep Learning
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Skin cancer detection using dermoscopic images with convolutional neural network.

Scientific reports Mar 1, 2025
Skin malignant melanoma is a high-risk tumor with low incidence but high mortality rates. Early detection and treatment are crucial for a cure. Machine learning studies have focused on classifying melanoma tumors, but these methods are cumbersome and...
Deep Learning Convolutional Neural Networks Early Detection of Cancer Melanoma, Cutaneous Malignant Melanoma Skin Neoplasms Dermoscopy Humans Neural Networks, Computer
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