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.
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.
Python-based machine learning and data science module from SFSU developed for the NIGMS Sandbox project
An application for creating, validating, reusing and extending sets of clinical codes.
MusicPsychologyToolbox
Live births in Scotland 2021 - Exercise on spatial vector data with R - RMarkdown file
Presentation about the "self-controlled case series (SCCS)" method.
State-Level Risk Factor Analysis of Mental Health Wellbeing
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.
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.
Machine learning diabetes prediction mini project
Healthcare Data Insights App This Streamlit application provides interactive visualizations and analyses of healthcare data. It includes modules for demographic, timeline, and treatment analysis, enabling users to explore patterns and gain insights from healthcare datasets.
Introduction to Data Collection Methods(IDCM)
A Collection of 120 Psychology Patients with 17 Essential Symptoms to Diagnose Mania Bipolar Disorder, Depressive Bipolar Disorder, Major Depressive Disorder, and Normal Individuals. The dataset contains the 17 essential symptoms psychiatrists use to diagnose the described disorders.
Simple IMC Calculator built in Flutter
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