Main repo including core data model, data marts, reference data, terminology, and the clinical concept library

A ready-to-use framework of the state-of-the-art models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, anomaly detection, and etc.

An experimental Clinical Quality Language execution engine for analyzing FHIR healthcare data at scale.

Hospital admission data was analyzed to accurately predict the patient’s Length of Stay at the time of admit so that the hospitals can optimize resources and function better.

Discover a curated collection of dynamic Power BI dashboards covering financial analytics, HR metrics, streaming service trends, real estate dynamics, and more. Meticulously designed for comprehensive data exploration, this repository continues to expand with new and impactful visualizations.

Power Pop Health is a collection of content intended to simplify the process of ingesting and prepping Healthcare Open Data using Azure data tools and Power BI. Moving forward the overarching theme will be data related to Population Health, but other sources pertinent to Healthcare will also be included.

In this repository, explore insightful solutions through exploratory data analysis focusing on mental health problems. Gain valuable insights into understanding and addressing key challenges in this critical domain.

A starter dbt project and synthetic claims dataset for trying out the Tuva Project.

This connector is a dbt project that maps Medicare CCLF claims data to the Tuva Input Layer.

An open source library for analysis of respiratory EMG

A web application that assists patients with reviewing objective quality indicators and subjective reviews together along with making an informed decision about their future care.

Maps Medicare LDS claims data to the Tuva Input Layer so you can easily run the Tuva Project.

The Tuva Project Docs i.e. where we write and share our knowledge about healthcare data and analytics.

Data sets for the healthyR package.

Hospital episodes can overlap or have gaps which can result in under or over counting. This package contains functions which can be used to rectify this common analytical issue in NHS data.

Statistical analysis of heart disease data project completed during my enrollment in the Data Science program through Thinkful.

Healthcare modelling using Python, Pandas and Dask

All of mine ML projects

A data and statistics analysis on the institutions in charge of healthcare in Mexico.