Skin burn identification is a very critical job to identify the burn location and its impact on the body. The current paper aims with the objective to identify the burn location and its impact so that the severity can be measured to provide effective treatment. The solution is derived using ...
Skin Lesion Classification and Detection Using Machine Learning Techniques: A Systematic Review Skin lesions are essential for the early detection and management of a number of dermatological disorders. Learning-based methods for skin lesion analysis ... TG Debelee - Diagnostics (2075-4418) 被引量:...
information. Machine learning-based approaches that classify the underlying skin condition and use the predicted skin condition to directly decide on a disease management (e.g., Han et al.21) may not well distinguish among different management decisions that exist within a single class. A managemen...
Lite-YOLOv8: a more lightweight algorithm for Tubercle Bacilli detection Yonghong Li Haiyang Qiu Jingqing Tang Medical & Biological Engineering & Computing(2025) Risk factors for scabies in hospital: a systematic review Dong-Hee Kim Yujin Kim ...
Early detection is critical! 2. Development process and Data The idea of this project is to construct a CNN model that can predict the probability that a specific mole can be malign. 2.1 Data: To train this model the data to use is a set of images from the International Skin Imaging Col...
Skin Cancer Prediction using Deep Learning Some of the goals of this study are to build a CNN model for skin cancer detection with over 80% accuracy, keep the false-negative rate below 10% ... K Vatekar,S Phapale,A Bhor,... - 《International Journal of Advanced Research in Science Com...
While, if we want to ensure the reliability and reproducibility of TERS measurements, we must consider optical properties, tip design, the operating environment and conditions, and the far-field scattering background. In the field of clinical skin detection, this might translate to uncertainty and ...
Early detection of skin cancer is very important as it is one of the dangerous form of cancer spreading vigorously among humans. With the advancement of mobile technology; mobile enabled skin cancer detection systems are really demanding but currently very few real time skin cancer detection systems...
Machine learning in dermatology: current applications, opportunities, and limitations. Dermatol. Ther. 10, 365–386 (2020). Article Google Scholar Dildar, M. et al. Skin cancer detection: a review using deep learning techniques[J]. Int. J. Environ. Res. Public Health 18, 5479 (2021). ...
Rapid advances in artificial intelligence, robotics, and remote healthcare have increased the demand for sustainable and high-performance wearable sensors.