The swiss army knife for discharge abstract database (DAD).

Patient Reported Information Multidimensional Exploration (PRIME) is an automated platform to investigate Online Support Group (a.k.a. health forums, online health groups) discussions for investigation of individualised patient behaviours and patient information, over time.

Milestone 2 project - Electronic Health Record Analysis and ICD Code Prediction

MortalityMinder: an R-based, multi-view interactive presentation examining county-level factors associated with midlife mortality trends.

Data analysis focusing on health problems

Machine learning project to predict obesity risk levels based on lifestyle and demographic data. This project utilizes advanced algorithms like CatBoost, LightGBM, and more to classify individuals into different obesity categories

The W4H Integrated Toolkit Repository provides a unified platform for managing, analyzing, and visualizing wearable health data using a suite of open-source tools and frameworks.

The app helps to analyze correlation between various weather parameters and symmetry of electrocardiographic T-wave

Predict a patients health with his medical report

A SAS analysis project on cardiovascular disease data

Mini Case Study is from Danny Ma's 8 Week SQL Challenge

Many institutions recognize the importance of athletes' behaviors across the 24-hour cycle, leading to increased monitoring on and off the field. Institutions often turn to consumer-grade activity monitors that allow for continuous tracking. This repository provides the user with valuable experience for analyzing data from such devices

FHIR server that transforms QuestionnaireResponses to OHDSI OMOP CDM.

Data analysis of concerning prevalence of heart disease and stroke given various health variables, such as Age, Smoking habits, Weight, among others.

Statistical study of various health related questions

In this notebook, we're going to analyse the data that made Semmelweis discover the importance of handwashing. Let's start by looking at the data that made Semmelweis realize that something was wrong with the procedures at Vienna General Hospital.

Developed a machine learning model for diabetes prediction, using patient data to provide early risk assessments and improve healthcare outcomes.