Skin Diseases

Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024

This study explores the utilization of Dermatoscopic synthetic data generated through stable diffusion models as a strategy for enhancing the robustness of machine learning model training. Synthetic data plays a pivotal role in mitigating challenges ...

Algorithms Dermoscopy Diffusion Humans Image Processing, Computer-Assisted Machine Learning Neural Networks, Computer Skin Diseases Skin Neoplasms

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Attention-aware Deep Learning Models for Dermoscopic Image Classification for Skin Disease Diagnosis.

Current medical imaging Jan 1, 2025

BACKGROUND: The skin, being the largest organ in the human body, plays a vital protective role. Skin lesions are changes in the appearance of the skin, such as bumps, sores, lumps, patches, and discoloration. If not identified and treated promptly, s...

Deep Learning Dermoscopy Humans Image Interpretation, Computer-Assisted Neural Networks, Computer Skin Diseases

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A skin disease classification model based on multi scale combined efficient channel attention module.

Scientific reports Feb 19, 2025

Skin diseases, a significant category in the medical field, have always been challenging to diagnose and have a high misdiagnosis rate. Deep learning for skin disease classification has considerable value in clinical diagnosis and treatment. This stu...

Algorithms Deep Learning Humans Neural Networks, Computer Skin Diseases

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Dermacen analytica: A novel methodology integrating multi-modal large language models with machine learning in dermatology.

International journal of medical informatics Mar 25, 2025

OBJECTIVE: To design, implement, evaluate, and quantify a novel and adaptable Artificial Intelligence-empowered methodology aimed at supporting a dermatologist's workflow in assessing and diagnosing skin conditions, leveraging AI's deep image analyti...

Artificial Intelligence Dermatology Humans Large Language Models Machine Learning Natural Language Processing Skin Diseases

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Enhancing skin disease classification leveraging transformer-based deep learning architectures and explainable AI.

Computers in biology and medicine Mar 20, 2025

Skin diseases affect over a third of the global population, yet their impact is often underestimated. Automating the classification of these diseases is essential for supporting timely and accurate diagnoses. This study leverages Vision Transformers,...

Databases, Factual Deep Learning Humans Neural Networks, Computer Skin Diseases

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FEGGNN: Feature-Enhanced Gated Graph Neural Network for robust few-shot skin disease classification.

Computers in biology and medicine Mar 9, 2025

Accurate and timely classification of skin diseases is essential for effective dermatological diagnosis. However, the limited availability of annotated images, particularly for rare or novel conditions, poses a significant challenge. Although few-sho...

Algorithms Diagnosis, Computer-Assisted Graph Neural Networks Humans Image Interpretation, Computer-Assisted Neural Networks, Computer Skin Diseases

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Skin lesion segmentation with a multiscale input fusion U-Net incorporating Res2-SE and pyramid dilated convolution.

Scientific reports Mar 7, 2025

Skin lesion segmentation is crucial for identifying and diagnosing skin diseases. Accurate segmentation aids in identifying and localizing diseases, monitoring morphological changes, and extracting features for further diagnosis, especially in the ea...

Algorithms Dermoscopy Humans Image Processing, Computer-Assisted Neural Networks, Computer Skin Skin Diseases Skin Neoplasms

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Predictive modeling and optimization in dermatology: Machine learning for skin disease classification.

Computers in biology and medicine Mar 3, 2025

The accurate diagnosis of skin diseases is crucial for effective patient management and treatment, yet traditional diagnostic methods often involve subjective interpretation and can lead to variability in outcomes. In this study, we harness the power...

Dermatology Diagnosis, Computer-Assisted Humans Machine Learning Skin Diseases Support Vector Machine

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Prediction of Patient Visits for Skin Diseases through Enhanced Evolutionary Computation and Ensemble Learning.

Journal of medical systems Apr 23, 2025

Skin diseases are an important global public health issue, causing significant health and psychological burdens. Predicting dermatology outpatient visits is essential for optimizing hospital resources and improving diagnosis and treatment methods. Ba...

Acne Vulgaris Algorithms China Ensemble Learning Humans Machine Learning Neural Networks, Computer Skin Diseases

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An attention based hybrid approach using CNN and BiLSTM for improved skin lesion classification.

Scientific reports May 5, 2025

Skin lesions remain a significant global health issue, with their incidence rising steadily over the past few years. Early and accurate detection is crucial for effective treatment and improving patient outcomes. This work explores the integration of...

Algorithms Humans Neural Networks, Computer Skin Diseases

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AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Derm-T2IM: Harnessing Synthetic Skin Lesion Data via Stable Diffusion Models for Enhanced Skin Disease Classification using ViT and CNN.

Attention-aware Deep Learning Models for Dermoscopic Image Classification for Skin Disease Diagnosis.

A skin disease classification model based on multi scale combined efficient channel attention module.

Dermacen analytica: A novel methodology integrating multi-modal large language models with machine learning in dermatology.

Enhancing skin disease classification leveraging transformer-based deep learning architectures and explainable AI.

FEGGNN: Feature-Enhanced Gated Graph Neural Network for robust few-shot skin disease classification.

Skin lesion segmentation with a multiscale input fusion U-Net incorporating Res2-SE and pyramid dilated convolution.

Predictive modeling and optimization in dermatology: Machine learning for skin disease classification.

Prediction of Patient Visits for Skin Diseases through Enhanced Evolutionary Computation and Ensemble Learning.

An attention based hybrid approach using CNN and BiLSTM for improved skin lesion classification.

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