AIMC Topic: Skin Neoplasms

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User and Developer Views on Using AI Technologies to Facilitate the Early Detection of Skin Cancers in Primary Care Settings: Qualitative Semistructured Interview Study.

JMIR cancer Jan 28, 2025
BACKGROUND: Skin cancers, including melanoma and keratinocyte cancers, are among the most common cancers worldwide, and their incidence is rising in most populations. Earlier detection of skin cancer leads to better outcomes for patients. Artificial ...
Adult Male Middle Aged Female Humans Early Detection of Cancer Artificial Intelligence Skin Neoplasms Aged Qualitative Research Interviews as Topic Primary Health Care
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LiteMamba-Bound: A lightweight Mamba-based model with boundary-aware and normalized active contour loss for skin lesion segmentation.

Methods (San Diego, Calif.) Jan 27, 2025
In the field of medical science, skin segmentation has gained significant importance, particularly in dermatology and skin cancer research. This domain demands high precision in distinguishing critical regions (such as lesions or moles) from healthy ...
Image Interpretation, Computer-Assisted Algorithms Skin Neoplasms Humans Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Skin
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Risk score stratification of cutaneous melanoma patients based on whole slide images analysis by deep learning.

Journal of the European Academy of Dermatology and Venereology : JEADV Jan 24, 2025
BACKGROUND: There is a need to improve risk stratification of primary cutaneous melanomas to better guide adjuvant therapy. Taking into account that haematoxylin and eosin (HE)-stained tumour tissue contains a huge amount of clinically unexploited mo...
Skin Neoplasms Aged Adult Prognosis Female Humans Melanoma Deep Learning Image Processing, Computer-Assisted Male Melanoma, Cutaneous Malignant Middle Aged Risk Assessment
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Advanced Deep Learning Models for Melanoma Diagnosis in Computer-Aided Skin Cancer Detection.

Sensors (Basel, Switzerland) Jan 21, 2025
The most deadly type of skin cancer is melanoma. A visual examination does not provide an accurate diagnosis of melanoma during its early to middle stages. Therefore, an automated model could be developed that assists with early skin cancer detection...
Dermoscopy Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Algorithms Deep Learning Humans Melanoma Neural Networks, Computer Skin Neoplasms
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Minimal sourced and lightweight federated transfer learning models for skin cancer detection.

Scientific reports Jan 21, 2025
One of the most fatal diseases that affect people is skin cancer. Because nevus and melanoma lesions are so similar and there is a high likelihood of false negative diagnoses challenges in hospitals. The aim of this paper is to propose and develop a ...
Humans Algorithms Melanoma Skin Neoplasms Deep Learning
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Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification.

PloS one Jan 16, 2025
Skin cancer is considered globally as the most fatal disease. Most likely all the patients who received wrong diagnosis and low-quality treatment die early. Though if it is detected in the early stages the patient has fairly good chance and the afore...
Image Processing, Computer-Assisted Skin Random Forest Humans Skin Neoplasms Neural Networks, Computer Deep Learning Algorithms Convolutional Neural Networks
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Diagnosis and prognosis of melanoma from dermoscopy images using machine learning and deep learning: a systematic literature review.

BMC cancer Jan 13, 2025
BACKGROUND: Melanoma is a highly aggressive skin cancer, where early and accurate diagnosis is crucial to improve patient outcomes. Dermoscopy, a non-invasive imaging technique, aids in melanoma detection but can be limited by subjective interpretati...
Dermoscopy Deep Learning Melanoma Skin Neoplasms Humans Machine Learning Prognosis
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The role of mitophagy-related genes in prognosis and immunotherapy of cutaneous melanoma: a comprehensive analysis based on single-cell RNA sequencing and machine learning.

Immunologic research Jan 11, 2025
Mitophagy, the selective degradation of mitochondria by autophagy, plays a crucial role in cancer progression and therapy response. This study aims to elucidate the role of mitophagy-related genes (MRGs) in cutaneous melanoma (CM) through single-cell...
Gene Regulatory Networks Immunotherapy Sequence Analysis, RNA Gene Expression Profiling Transcriptome Single-Cell Analysis Gene Expression Regulation, Neoplastic Melanoma, Cutaneous Malignant Mitophagy Machine Learning Prognosis Melanoma Skin Neoplasms Tumor Microenvironment Biomarkers, Tumor Humans
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Boosting skin cancer diagnosis accuracy with ensemble approach.

Scientific reports Jan 8, 2025
Skin cancer is common and deadly, hence a correct diagnosis at an early age is essential. Effective therapy depends on precise classification of the several skin cancer forms, each with special traits. Because dermoscopy and other sophisticated imagi...
Humans Neural Networks, Computer Machine Learning Support Vector Machine Algorithms Skin Neoplasms Dermoscopy
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Multi-scale feature fusion of deep convolutional neural networks on cancerous tumor detection and classification using biomedical images.

Scientific reports Jan 7, 2025
In the present scenario, cancerous tumours are common in humans due to major changes in nearby environments. Skin cancer is a considerable disease detected among people. This cancer is the uncontrolled evolution of atypical skin cells. It occurs when...
Algorithms Skin Neoplasms Deep Learning Humans Image Processing, Computer-Assisted Neural Networks, Computer Image Interpretation, Computer-Assisted
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