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

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.

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

Build a CNN based model which can accurately detect melanoma

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

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 Web Application that uses Computer Vision and Deep Learning to identify the three highest probability diagnoses for a skin lesion image input by the User.

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

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.

We attempt to change how you look at Medical Diagnosis

Skin lesion classification, using Keras and the ISIC 2020 dataset

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

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

Predict your diseases based on the symptoms provided And Image Processing technique is used to predict the skin cancer

Pretraining and finetuning different vision transformer models on the ImageNet and Ham10000 dataset

Skin Cancer Detection project is a web application developed to detect skin cancer utilizing deep learning techniques.

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

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

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