Awesome artificial intelligence in cancer diagnostics and oncology

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.

Tumor prediction from microarray data using 10 machine learning classifiers. Feature extraction from microarray data using various feature extraction algorithms.

As part of this project, I have used Machine Learning (classification) algorithms for classification of tumors in Human Breasts as Non-Cancerous/ Benign or Cancerous/ Malignant tumors.

Glioblasted is a machine learning model to assist in the detection of glioblastoma multiforme, a high-grade, aggressive form of central nervous system cancer.

Empowering early cancer detection through advanced machine learning models. Our project focuses on predicting oral, cervical, and brain tumors using a blend of image and risk factor data. Join us in the journey to enhance healthcare outcomes through cutting-edge technology

This project uses machine learning classifier algorithms to predict whether the patient is suffering from cancer or not.

Lung Cancer Prediction Model: Leverage the power of deep learning with this TensorFlow-based project. Trained on a dataset of lung X-Ray images, the model accurately predicts cancer cases. Easily integrate and utilize the model for early detection. #HealthTech #MachineLearning

The following repository consists of some Fundamental Data Science and Machine Learning Prediction Models created using available datasets from Github itself using Google Colab Notebook

Cancer Prediction using ML in MATLAB/Octave

TensorFlow/Keras examples and notes.

This repository houses a workflow that uses biological feature trees to segregate cancer RNA-seq datasets, then it trains machine learning models to predict the presence or absence of known, cancer-associated DNA-level mutations.

This repository presents a project describing a quantum simulator algorithm for early cancer prediction. The QisKit and QisKit Aer libraries were used for the experiment. At the core lies Python as the programming language.

CARES (Cancer Awareness and Risk Evaluation by Self-Assessment) monitors real-time blood data through regular CBP (Complete Blood Picture) updates to assess cancer risk. It also offers comprehensive information on cancer symptoms, treatments, and preventive measures.

Prediction of Cancer Using Machine Learning Model

Extreme gradient boosting algorithm (Xgboost)

This Website is basically detect Metastasis and Malignant Cancer.

Breast Cancer Survival Prediction | Machine Learning Course Project, Fall 2022

This project provides the classification of DNA sequences for Breast cancer prediction which into promoter regions associated. Using machine learning and deep learning techniques, I analyze and try to predict sequence data for negative and positive answers in cancer prediction.

This project focuses on predicting breast cancer using machine learning models through cross-validation techniques. The dataset utilized in this study is the Breast Cancer Wisconsin (Diagnostic) dataset.