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

Build a CNN based model which can accurately detect melanoma

A menu based multiple chronic disease detection system which will detect if a person is suffering from a severe disease by taking an essential input image.

We attempt to change how you look at Medical Diagnosis

Skin Cancer Detection Web App using Flask Framework deployed on the Heroku server.

ONCO is a cancer diagnosis/prognosis mobile application focused on the 3 main cancers of the thoracic region (Breast, Lung & Skin)

🎗 This is an Android app to detect melanoma skin cancer using tensorflow mobile.

Multiclass skin cancer detection using explainable AI for checking the models' robustness

The dataset consists of 10015 dermatoscopic images which can serve as a training set for academic machine learning purposes. The objective to build deep learning model to classify given query image into one of the 7 different classes of skin cancer.

Skin lesion classification, using Keras and the ISIC 2020 dataset

A libre skin cancer detection app

3-layered approach to detecting cancer, melanoma and allergies with state-of-the-art Tensorflow models, integrated into an app with exciting features using Flutter Android development framework.

A mobile skin cancer detection application that won an international price of $10,000

Cross-platform smartphone app capable of detecting skin cancer lesions using Computer Vision.

This app contains and skin cancer android app whose model is created using transfer learning with inception_v3

This repository contains Python code for generating a skin cancer detection model and utilizing it to detect skin cancer from user-inputted images or videos. The model architecture follows a sequential structure consisting of convolutional and pooling layers, with the final output layer using a sigmoid activation function.

Skin Lesion Classifier: a skin lesion analysis towards melanoma detection.

Explainable AI (XAI) project aiming to show undesired bias in skin cancer predictions models trained on the ISIC dataset