AIMC Topic: Skin Neoplasms
Clear Filters Showing 131 to 140 of 485 articles
Trained neural networking framework based skin cancer diagnosis and categorization using grey wolf optimization.
Scientific reports
Apr 24, 2024
Skin Cancer is caused due to the mutational differences in epidermis hormones and patch appearances. Many studies are focused on the design and development of effective approaches in diagnosis and categorization of skin cancer. The decisions are made...
A novel SpaSA based hyper-parameter optimized FCEDN with adaptive CNN classification for skin cancer detection.
Scientific reports
Apr 23, 2024
Skin cancer is the most prevalent kind of cancer in people. It is estimated that more than 1 million people get skin cancer every year in the world. The effectiveness of the disease's therapy is significantly impacted by early identification of this ...
People Also Ask: What Do Internet Users Want to Know About Mohs Surgery, and What Can Artificial Intelligence Tell Them?
Dermatologic surgery : official publication for American Society for Dermatologic Surgery [et al.]
Apr 17, 2024
Comparing preferences for skin cancer screening: AI-enabled app vs dermatologist.
Social science & medicine (1982)
Apr 15, 2024
BACKGROUND AND AIM: Skin cancer is a major public health issue. While self-examinations and professional screenings are recommended, they are rarely performed. Mobile health (mHealth) apps utilising artificial intelligence (AI) for skin cancer screen...
Exploring a specialized programmed-cell death patterns to predict the prognosis and sensitivity of immunotherapy in cutaneous melanoma via machine learning.
Apoptosis : an international journal on programmed cell death
Apr 14, 2024
The mortality and therapeutic failure in cutaneous melanoma (CM) are mainly caused by wide metastasis and chemotherapy resistance. Meanwhile, immunotherapy is considered a crucial therapy strategy for CM patients. However, the efficiency of currently...
Automated melanoma detection. An algorithm inspired from human intelligence characterizing disordered pattern of melanocytic lesions improving a convolutional neural network.
Journal of the American Academy of Dermatology
Apr 12, 2024
Histological interpretation of spitzoid tumours: an extensive machine learning-based concordance analysis for improving decision making.
Histopathology
Apr 12, 2024
The histopathological classification of melanocytic tumours with spitzoid features remains a challenging task. We confront the complexities involved in the histological classification of these tumours by proposing machine learning (ML) algorithms tha...
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...
Current safeguards, risk mitigation, and transparency measures of large language models against the generation of health disinformation: repeated cross sectional analysis.
BMJ (Clinical research ed.)
Mar 20, 2024
OBJECTIVES: To evaluate the effectiveness of safeguards to prevent large language models (LLMs) from being misused to generate health disinformation, and to evaluate the transparency of artificial intelligence (AI) developers regarding their risk mit...
Dermatoscopic features and potential pitfalls of artificial intelligence-based analysis of benign acral pigmented lesions in Black patients: A multicenter observational study.
Journal of the American Academy of Dermatology
Mar 19, 2024
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