AIMC Topic: Skin Neoplasms

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Identifying novel circadian rhythm biomarkers for diagnosis and prognosis of melanoma by an integrated bioinformatics and machine learning approach.

Aging
Melanoma is a highly malignant skin tumor with poor prognosis. Circadian rhythm is closely related to melanoma pathogenesis. This study aimed to identify key circadian rhythm genes (CRGs) in melanoma and explore their potential as diagnostic and prog...

Systematic review of approaches to detection and classification of skin cancer using artificial intelligence: Development and prospects.

Computers in biology and medicine
In recent years, there has been a significant improvement in the accuracy of the classification of pigmented skin lesions using artificial intelligence algorithms. Intelligent analysis and classification systems are significantly superior to visual d...

Enhancing Skin Cancer Diagnosis Using Swin Transformer with Hybrid Shifted Window-Based Multi-head Self-attention and SwiGLU-Based MLP.

Journal of imaging informatics in medicine
Skin cancer is one of the most frequently occurring cancers worldwide, and early detection is crucial for effective treatment. Dermatologists often face challenges such as heavy data demands, potential human errors, and strict time limits, which can ...

Optimized attention-induced multihead convolutional neural network with efficientnetv2-fostered melanoma classification using dermoscopic images.

Medical & biological engineering & computing
Melanoma is an uncommon and dangerous type of skin cancer. Dermoscopic imaging aids skilled dermatologists in detection, yet the nuances between melanoma and non-melanoma conditions complicate diagnosis. Early identification of melanoma is vital for ...

Automatized self-supervised learning for skin lesion screening.

Scientific reports
Melanoma, the deadliest form of skin cancer, has seen a steady increase in incidence rates worldwide, posing a significant challenge to dermatologists. Early detection is crucial for improving patient survival rates. However, performing total body sc...

A real-time augmented reality system integrated with artificial intelligence for skin tumor surgery: experimental study and case series.

International journal of surgery (London, England)
BACKGROUND: Skin tumors affect many people worldwide, and surgery is the first treatment choice. Achieving precise preoperative planning and navigation of intraoperative sampling remains a problem and is excessively reliant on the experience of surge...

A model for skin cancer using combination of ensemble learning and deep learning.

PloS one
Skin cancer has a significant impact on the lives of many individuals annually and is recognized as the most prevalent type of cancer. In the United States, an estimated annual incidence of approximately 3.5 million people receiving a diagnosis of sk...

Machine learning-derived immunosenescence index for predicting outcome and drug sensitivity in patients with skin cutaneous melanoma.

Genes and immunity
The functions of immunosenescence are closely related to skin cutaneous melanoma (SKCM). The aim of this study is to uncover the characteristics of immunosenescence index (ISI) to identify novel biomarkers and potential targets for treatment. Firstly...

Empirical validation of Conformal Prediction for trustworthy skin lesions classification.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Uncertainty quantification is a pivotal field that contributes to realizing reliable and robust systems. It becomes instrumental in fortifying safe decisions by providing complementary information, particularly within high-r...

Automated Prediction of Malignant Melanoma using Two-Stage Convolutional Neural Network.

Archives of dermatological research
PURPOSE: A skin lesion refers to an area of the skin that exhibits anomalous growth or distinctive visual characteristics compared to the surrounding skin. Benign skin lesions are noncancerous and generally pose no threat. These irregular skin growth...