AIMC Topic: Skin Neoplasms

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What Are Patients' Perceptions and Attitudes Regarding the Use of Artificial Intelligence in Skin Cancer Screening and Diagnosis? Narrative Review.

The Journal of investigative dermatology
Artificial intelligence (AI) could enable early diagnosis of skin cancer; however, how AI should be implemented in clinical practice is debated. This narrative literature review (16 studies; 2012-2024) explored patient perceptions of AI in skin cance...

A fuzzy rank-based deep ensemble methodology for multi-class skin cancer classification.

Scientific reports
Skin cancer is widespread and can be potentially fatal. According to the World Health Organisation (WHO), it has been identified as a leading cause of mortality. It is essential to detect skin cancer early so that effective treatment can be provided ...

A multi-stage multi-modal learning algorithm with adaptive multimodal fusion for improving multi-label skin lesion classification.

Artificial intelligence in medicine
Skin cancer is frequently occurring and has become a major contributor to both cancer incidence and mortality. Accurate and timely diagnosis of skin cancer holds the potential to save lives. Deep learning-based methods have demonstrated significant a...

A promising AI based super resolution image reconstruction technique for early diagnosis of skin cancer.

Scientific reports
Skin cancer can be prevalent in people of any age group who are exposed to ultraviolet (UV) radiation. Among all other types, melanoma is a notable severe kind of skin cancer, which can be fatal. Melanoma is a malignant skin cancer arising from melan...

A robust deep learning framework for multiclass skin cancer classification.

Scientific reports
Skin cancer represents a significant global health concern, where early and precise diagnosis plays a pivotal role in improving treatment efficacy and patient survival rates. Nonetheless, the inherent visual similarities between benign and malignant ...

Precision and efficiency in skin cancer segmentation through a dual encoder deep learning model.

Scientific reports
Skin cancer is a prevalent health concern, and accurate segmentation of skin lesions is crucial for early diagnosis. Existing methods for skin lesion segmentation often face trade-offs between efficiency and feature extraction capabilities. This pape...

Machine learning predicts selected cat diseases using insurance data amid challenges in interpretability.

American journal of veterinary research
OBJECTIVE: To develop models for prediction of the onset of specific diseases in cats using pet insurance data and to evaluate their predictive performance.

A comprehensive analysis of deep learning and transfer learning techniques for skin cancer classification.

Scientific reports
Accurately and early diagnosis of melanoma is one of the challenging tasks due to its unique characteristics and different shapes of skin lesions. So, in order to solve this issue, the current study examines various deep learning-based approaches and...

Optimizing Skin Cancer Diagnosis: A Modified Ensemble Convolutional Neural Network for Classification.

Microscopy research and technique
Skin cancer is recognized as one of the most harmful cancers worldwide. Early detection of this cancer is an effective measure for treating the disease efficiently. Traditional skin cancer detection methods face scalability challenges and overfitting...

Towards unbiased skin cancer classification using deep feature fusion.

BMC medical informatics and decision making
This paper introduces SkinWiseNet (SWNet), a deep convolutional neural network designed for the detection and automatic classification of potentially malignant skin cancer conditions. SWNet optimizes feature extraction through multiple pathways, emph...