Point of care system for AMPATH clinics
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Updated
Jun 24, 2026 - TypeScript
Point of care system for AMPATH clinics
Social platform for people with chronic diseases
This project aims to develop an embedded system that monitors chronic disease patients who need frequent medical check-ups.
Deep learning for comprehensively assessing chronic gastritis from whole-slide images: a multicenter, retrospective cohort study
This site provides information to support data users with developing custom queries in the Multi-State EHR-Based Network for Disease Surveillance (MENDS).
Human survival post-LGM relied on adaptation, cooperation, and innovation. Neanderthal and Denisovan genes shaped immunity and metabolism, but uniform modern diets clash with these traits, fueling chronic disease. Embracing diversity can drive health and resilience.
A Do-It-Yourself AI-based module for your personalized interstitial glucose 30-min prediction! Compatible with different OS through Dockerization. Your data, your personalized model, and the execution are performed locally, without sharing anything with anyone! This module has been validated with real CGM data collected from 29 people with T1D.
BioMedical Language Processing with ELECTRA
Chronic Disease Control Data Analysis and Visualization
My first repository on GitHub
Analysis of publicly available data to identify areas with food access challenges. Study of a link between food insecurity and prevalence of chronic conditions.
Information on Thriving with Long-COVID and Other Chronic Illness
Predicting Chronic Disease Onset in Older Adults: A machine learning study using The Irish Longitudinal Study on Ageing (TILDA)
Final Project for Geospatial Datascience in Python
This repository contains an EDA dashboard and some key visualizations providing insights into the US Chronic Disease Indicator dataset and disease trends
Open-access scholarly review on multimorbidity / Открытый научный обзор по мультиморбидности
Exploratory analysis and dashboard of chronic disease trends in Guanajuato, Mexico, based on ENSADUL health surveys 2020–2022.
Tealth provides actionable, accessible health insights for predicted long-term health risks, powered by ML.
Analysis of core Chronic Diseases in Northern Nigeria is a group project demo performed by trainees at GIZ sponsored Data Science training program by COVEN LABS. The Data was gotten from kaggle.com and was prepared by Emmanuel Odelanmi who was trying to predict Meningitis occurrence in individuals using Machine Learning. The project is to advice…
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