BCDU-Net : Medical Image Segmentation

Brain Tumor Detection Using Convolutional Neural Networks.

AI-based pathology predicts origins for cancers of unknown primary - Nature

Health Check ✔ is a Machine Learning Web Application made using Flask that can predict mainly three diseases i.e. Diabetes, Heart Disease, and Cancer.

Awesome artificial intelligence in cancer diagnostics and oncology

1st to MICCAI DigestPath2019 challenge (https://digestpath2019.grand-challenge.org/Home/) on colonoscopy tissue segmentation and classification task. (MICCAI 2019) https://teacher.bupt.edu.cn/zhuchuang/en/index.htm

Breast Cancer Detection Using Machine Learning

This CNN is capable of diagnosing breast cancer from an eosin stained image. This model was trained using 400 images. It has an accuracy of 80%

Segmentation of skin cancers on ISIC 2017 challenge dataset.

This application aims to early detection of lung cancer to give patients the best chance at recovery and survival using CNN Model.

simple brain tumor detection using DCNNs

This project uses Deep learning concept in detection of Various Deadly diseases. It can Detect 1) Lung Cancer 2) Covid-19 3)Tuberculosis 4) Pneumonia. It uses CT-Scan and X-ray Images of chest/lung in detecting the disease. It has a Accuracy between 50%-80%. It can take input in any Image format or through Live videos and provide accurate output…

Cancer Detection from Microscopic Images by Fine-tuning Pre-trained Models ("Inception") for new class labels

Trained a Multi-Layer Perceptron, AlexNet and pre-trained InceptionV3 architectures on NVIDIA GPUs to classify Brain MRI images into meningioma, glioma, pituitary tumor which are cancer classes and those images which are healthy into no tumor class.

CNN histopathologic tumor identifier.

Tissue Cancer Segmentation project using multiple segmentation networks

Nuclei segmentation and classification (Cancer cells)

Lung nodule detection- LUNA 16

tumor detection and segmentation with brain MRI with CNN and U-net algorithm

Machine learning techniques can be used to overcome these drawbacks which are cause due to the high dimensions of the data. So in this project I am using machine learning algorithms to predict the chances of getting cancer.