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.

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

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.

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.

A machine learning-based web app that predicts whether a breast tumor is Benign or Malignant using 29 medical features. Users can input data manually or upload a PDF report for automatic feature extraction. Built with Flask, Bootstrap, and PyMuPDF.

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

TensorFlow/Keras examples and notes.

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.

An ML-based project for predicting cancer using Logistic Regression and visualizing performance metrics.

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

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

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

Cancer Prediction using ML in MATLAB/Octave

Prediction of Cancer Using Machine Learning Model

The primary objective is the precise classification of mammograms into cancerous and non-cancerous categories, utilizing advanced Deep Learning. Additionally, a secondary focus involves the classification of cancerous mammograms based on the stages of cancer.

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.

Modelo preditivo do tempo de sobrevida de pacientes com câncer de pulmão de células não pequenas

Prediction of colorectal cancer (CRC) phenotype based on Microbiome Metagenomics