AIMC Topic: Skin Neoplasms
Clear Filters Showing 141 to 150 of 485 articles
SASAN: ground truth for the effective segmentation and classification of skin cancer using biopsy images.
Diagnosis (Berlin, Germany)
Mar 18, 2024
OBJECTIVES: Early skin cancer diagnosis can save lives; however, traditional methods rely on expert knowledge and can be time-consuming. This calls for automated systems using machine learning and deep learning. However, existing datasets often focus...
Enhancing skin lesion classification with advanced deep learning ensemble models: a path towards accurate medical diagnostics.
Current problems in cancer
Mar 13, 2024
Skin cancer, including the highly lethal malignant melanoma, poses a significant global health challenge with a rising incidence rate. Early detection plays a pivotal role in improving survival rates. This study aims to develop an advanced deep learn...
Review of the application of the most current sophisticated image processing methods for the skin cancer diagnostics purposes.
Archives of dermatological research
Mar 6, 2024
This paper presents the most current and innovative solutions applying modern digital image processing methods for the purpose of skin cancer diagnostics. Skin cancer is one of the most common types of cancers. It is said that in the USA only, one in...
Echoes of images: multi-loss network for image retrieval in vision transformers.
Medical & biological engineering & computing
Mar 4, 2024
This paper introduces a novel approach to enhance content-based image retrieval, validated on two benchmark datasets: ISIC-2017 and ISIC-2018. These datasets comprise skin lesion images that are crucial for innovations in skin cancer diagnosis and tr...
Combining artificial intelligence and human expertise for more accurate dermoscopic melanoma diagnosis: A 2-session retrospective reader study.
Journal of the American Academy of Dermatology
Feb 29, 2024
Patient and dermatologists' perspectives on augmented intelligence for melanoma screening: A prospective study.
Journal of the European Academy of Dermatology and Venereology : JEADV
Feb 27, 2024
BACKGROUND: Artificial intelligence (AI) shows promising potential to enhance human decision-making as synergistic augmented intelligence (AuI), but requires critical evaluation for skin cancer screening in a real-world setting.
LAMA: Lesion-Aware Mixup Augmentation for Skin Lesion Segmentation.
Journal of imaging informatics in medicine
Feb 26, 2024
Deep learning can exceed dermatologists' diagnostic accuracy in experimental image environments. However, inaccurate segmentation of images with multiple skin lesions can be seen with current methods. Thus, information present in multiple-lesion imag...
Machine learning developed an intratumor heterogeneity signature for predicting prognosis and immunotherapy benefits in skin cutaneous melanoma.
Melanoma research
Feb 16, 2024
Intratumor heterogeneity (ITH) is defined as differences in molecular and phenotypic profiles between different tumor cells and immune cells within a tumor. ITH was involved in the cancer progression, aggressiveness, therapy resistance and cancer rec...
Basal Cell Carcinoma Diagnosis with Fusion of Deep Learning and Telangiectasia Features.
Journal of imaging informatics in medicine
Feb 8, 2024
In recent years, deep learning (DL) has been used extensively and successfully to diagnose different cancers in dermoscopic images. However, most approaches lack clinical inputs supported by dermatologists that could aid in higher accuracy and explai...
Fusion between an Algorithm Based on the Characterization of Melanocytic Lesions' Asymmetry with an Ensemble of Convolutional Neural Networks for Melanoma Detection.
The Journal of investigative dermatology
Jan 29, 2024
Melanoma is still a major health problem worldwide. Early diagnosis is the first step toward reducing its mortality, but it remains a challenge even for experienced dermatologists. Although computer-aided systems have been developed to help diagnosis...
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