Python package for managing OHDSI clinical data models. Includes support for LLM based plain text queries!
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Updated
Dec 23, 2024 - Python
Python package for managing OHDSI clinical data models. Includes support for LLM based plain text queries!
Using machine learning models to predict if patients have chronic kidney disease based on a few features. The results of the models are also interpreted to make it more understandable to health practitioners.
Python-based machine learning and data science module from SFSU developed for the NIGMS Sandbox project
The NHANES Data 'API' is a Python tool that simplifies access to the National Health and Nutrition Examination Survey (NHANES) dataset. This project provides an easy-to-use API to retrieve NHANES data, helping researchers, data scientists, health professionals, and other stakeholders access these valuable datasets.
An application for creating, validating, reusing and extending sets of clinical codes.
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This project implements a decision tree model built from scratch without using any ML libraries/frameworks to classify patients as either containing diabetic retinopathy or not.
Objective, create an intuitive and user-friendly web-based application for visualizing and exploring NHANES data. This dashboard will enable users, including those with limited or no Python programming experience, to interact with NHANES data and generate informative visualizations to gain insights into various health-related aspects.
Simple IMC Calculator built in Flutter
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