AIMC Topic: Skin Neoplasms

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Comprehensive analysis of clinical images contributions for melanoma classification using convolutional neural networks.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) May 1, 2024
BACKGROUND: Timely diagnosis plays a critical role in determining melanoma prognosis, prompting the development of deep learning models to aid clinicians. Questions persist regarding the efficacy of clinical images alone or in conjunction with dermos...
Female Melanoma Humans Neural Networks, Computer Deep Learning ROC Curve Image Interpretation, Computer-Assisted Sensitivity and Specificity Skin Neoplasms Male Dermoscopy
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Utility of Artificial Intelligence in Patient Education: An Appraisal of Mohs Surgery Information Generated by ChatGPT-3.5 and ChatGPT-4.

Journal of drugs in dermatology : JDD May 1, 2024
Patient Education as Topic Mohs Surgery Artificial Intelligence Skin Neoplasms Humans
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Melanocytic lesions: How to navigate variations in human and artificial intelligence.

Journal of the European Academy of Dermatology and Venereology : JEADV May 1, 2024
Melanoma Humans Skin Neoplasms Artificial Intelligence
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Natural language processing to automate a web-based model of care and modernize skin cancer multidisciplinary team meetings.

The British journal of surgery Jan 3, 2024
BACKGROUND: Cancer multidisciplinary team (MDT) meetings are under intense pressure to reform given the rapidly rising incidence of cancer and national mandates for protocolized streaming of cases. The aim of this study was to validate a natural lang...
Humans Retrospective Studies Skin Neoplasms Internet Natural Language Processing Patient Care Team
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SkinLiTE: Lightweight Supervised Contrastive Learning Model for Enhanced Skin Lesion Detection and Disease Typification in Dermoscopic Images.

Current medical imaging Jan 1, 2024
INTRODUCTION: This study introduces SkinLiTE, a lightweight supervised contrastive learning model tailored to enhance the detection and typification of skin lesions in dermoscopic images. The core of SkinLiTE lies in its unique integration of supervi...
Dermoscopy Skin Supervised Machine Learning Humans Image Interpretation, Computer-Assisted Skin Neoplasms
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Automated cutaneous squamous cell carcinoma grading using deep learning with transfer learning.

Romanian journal of morphology and embryology = Revue roumaine de morphologie et embryologie Jan 1, 2024
INTRODUCTION: Histological grading of cutaneous squamous cell carcinoma (cSCC) is crucial for prognosis and treatment decisions, but manual grading is subjective and time-consuming.
Deep Learning Neoplasm Grading Skin Neoplasms Carcinoma, Squamous Cell Humans
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Deep learning approach for skin melanoma and benign classification using empirical wavelet decomposition.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2024
BACKGROUND: Melanoma is a malignant skin cancer that causes high mortality. Early detection of melanoma can save patients' lives. The features of the skin lesion images can be extracted using computer techniques to differentiate early between melanom...
Humans Melanoma Deep Learning Skin Neoplasms Wavelet Analysis
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Differentiation and risk stratification of basal cell carcinoma with deep learning on histopathologic images and measuring nuclei and tumor microenvironment features.

Skin research and technology : official journal of International Society for Bioengineering and the Skin (ISBS) [and] International Society for Digital Imaging of Skin (ISDIS) [and] International Society for Skin Imaging (ISSI) Jan 1, 2024
BACKGROUND: Nuclear pleomorphism and tumor microenvironment (TME) play a critical role in cancer development and progression. Identifying most predictive nuclei and TME features of basal cell carcinoma (BCC) may provide insights into which characteri...
Carcinoma, Basal Cell Risk Assessment Humans Deep Learning Skin Neoplasms Tumor Microenvironment
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Reduction of overfitting on the highly imbalanced ISIC-2019 skin dataset using deep learning frameworks.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: With the rapid growth of Deep Neural Networks (DNN) and Computer-Aided Diagnosis (CAD), more significant works have been analysed for cancer related diseases. Skin cancer is the most hazardous type of cancer that cannot be diagnosed in th...
Diagnosis, Computer-Assisted Deep Learning Nevus Neural Networks, Computer Skin Neoplasms Humans
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[MOCK MOLE: PRODUCING SYNTHETIC IMAGES THAT RECAPITULATE CONFOCAL PATTERNS OF MELANOCYTIC NEVI VIA DEEP-LEARNING MODELS].

Harefuah Dec 1, 2023
INTRODUCTION: Melanocytic nevi present microscopic patterns, which differ in their associated melanoma risk, and can be non-invasively recognized under Reflectance Confocal Microscopy (RCM).
Deep Learning Image Interpretation, Computer-Assisted Microscopy, Confocal Melanoma Humans Nevus, Pigmented Skin Neoplasms
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