Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification on HAM10000 dataset largescale data.

[MICCAI 2023] ECL: Class-Enhancement Contrastive Learning for Long-tailed Skin Lesion Classification

Official implementation of MICCAI2024 paper "Evidential Concept Embedding Models: Towards Reliable Concept Explanations for Skin Disease Diagnosis"

AI-based localization and classification of skin disease with erythema

Dermatrix is an AI-powered tool designed to help identify and provide information about common skin conditions. The application uses deep learning technology to analyze images of skin and compare them against a database of known skin diseases.

Data quality analysis of DermaMNIST (MedMNIST), HAM10000, and Fitzpatrick17k datasets

Predicting type of Skin Disease using CNN's . Deployed using Flask

Deep learning–powered platform for skin disease image classification and symptom-based disease prediction using a conversational LLM chatbot. Combines computer vision (MobileNetV2, EfficientNet) with natural language processing for interactive, user-friendly medical guidance.

Skin Lesion Classification On Imbalanced Data Using Deep Learning With Soft Attention

A small Android application that determines a skin disease by a photo

MERN Stack Web Application "EpiDetect" which uses a fine-tuned ResNet50 model for skin disease detection.

AI-powered skin disease classification system using a fine-tuned ResNet CNN with Grad-CAM explainability. Built with PyTorch and Streamlit to predict 8 skin conditions and visualize model attention for transparent, confidence-aware predictions.

A Hybrid Deep Learning Model using ViT and EfficientNetB0 for skin lesion classification on the HAM10000 dataset. It leverages data augmentation and early stopping to improve accuracy and reduce overfitting.

This repo contains the notebooks regarding our deep learning based image recognition projects with my students in Spelman College

disease detection model using ML model and transfer learning

A comprehensive deep learning-based system for the automated classification of skin diseases, leveraging convolutional neural networks to assist healthcare professionals in early diagnosis and treatment.

In this project i've built a CNN to classify skin diseases from images.

Skin Disease Detection Web App

An Effective Classification of Skin Infection using Deep Learning Techniques

No description provided.

This repository provides a deep learning-based approach to diagnose Melasma skin disease. By leveraging the power of deep neural networks, specifically VGGNet16, ResNet50, and AlexNet, this project aims to accurately classify Melasma images.

Skin Disease Classifier

A comprehensive, full-stack healthcare platform that leverages advanced AI and machine learning for intelligent skin health analysis, enabling early detection, personalized treatment recommendations, and seamless integration with telemedicine services.

A project that uses deep learning (CNN) to detect skin diseases from images.

skin disease classification using YOLOv8

This project focuses on the recognition and analysis of various skin diseases, including cancer and Vitiligo, using advanced image processing techniques and machine learning models in Matlab.

A machine learning-based system for detecting and classifying skin diseases through image analysis, utilizing deep learning models and classification pipelines.

This project focuses on building a model that predicts the age and contrasts amongst the medical images of skin diseases of 9 types. The dataset was taken from kaggle and was devided into train and validation images..