prognosis

This is a reposotory that includes paper、code and datasets about domain generalization-based fault diagnosis and prognosis. (基于领域泛化的故障诊断和预测)

Programming assignments, labs and quizzes from all courses in the Coursera AI for Medicine Specialization offered by deeplearning.ai

This repository contains code that implement common machine learning algorithms for remaining useful life (RUL) prediction.

Unified PHM framework for Remaining Useful Life (RUL) prediction, fault diagnosis, fault detection, and anomaly detection for bearings, turbofan engines, and other industrial systems.

Data sets on prognosis and health management（PHM相关数据集）

Medical Images processing

Identification of heterogeneous biomarkers for breast cancer using Clustering and PageRank algorithms (bioinformatics)

This is the official repository of the R package metamisc

deeplearning.ai - AI for Medicine Specialization (Andrew Ng, Pranav Rajpurkar)

AI application that can predict the survival of patients with heart failure using 12 clinical features.

In this competition, we’ll predict a patient’s severity of decline in lung function based on a CT scan of their lungs. We’ll determine lung function based on output from a spirometer, which measures the volume of air inhaled and exhaled.

Machine Learning for the Visualization of Alzheimer's Disease

Classification and Segmentation: Diagnose diseases from x-rays and 3D MRI brain images. Predict patient survival rates more accurately using tree-based models. Estimate treatment effects on patients using data from randomized trials.

Python-based tool for Quality Assurance of Varian TrueBeam MLCs

Classifying covid positive and negative cases in ct-scan images. Though the data is not large enough, it can be processed and make prediction from the model. Images are quite similar thus the task became much complicated.

DecenniumClinic is a reproducible Python stack for epidemiology-style cohorts: validation → imputation-in-pipeline random forests → Harrell’s C tuning, plus /health, /ready, and curl-friendly APIs. Built for methods research, not patient care.

Prognosis models and apps derived from the Ebola IMC dataset

Assignment for the AI for Medicine Specialization course.(1:Build and Evaluate a Linear Risk model/ 2:Risk Models Using Tree-based Models/ 3:Survival Estimates that Varies with Time/ 4:Cox Proportional Hazards and Random Survival Forests)

This repository contains the notes, codes, assignments, quizzes and other additional materials about the course "AI for Medical Prognosis" from DeepLearning.AI Coursera.

A computational framework to quantify individual-level NMD efficiency and assess its variability across human tissues, tumors and individuals using RNA-seq and WES data