Distributed Machine Learning for Bio-marker Prediction from Big Data Stream collected from Multi-modal Wearable Sensor Data
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Updated
Mar 25, 2017 - Python
Distributed Machine Learning for Bio-marker Prediction from Big Data Stream collected from Multi-modal Wearable Sensor Data
R package to assess and evaluate longitudinal mHealth sensor data.
A curated list of awesome Digital Global Health resources and software.
R package to support data io, manipulation and visualization for mhealth specification
Prognosis models and apps derived from the Ebola IMC dataset
👀 Drishti-EMR - openmrs-module-drishti
wearablecompute is an open source Python package containing over 50 data and domain-driven features that can be computed from wearables and mHealth sensor data.
wearablecompute is an open source Python package containing over 50 data and domain-driven features that can be computed from wearables and mHealth sensor data.
A light-weight simulator used to illustrate the use of Delay Tolerant Networks as a supplement for Cloud Connectivity for Rural Remote Patient Monitoring.
Mobile Health (mHealth) Viral Diagnostics Enabled with Adaptive Adversarial Learning.
An android based app for tracking your mental health
This repo contains the source code and a benchmark for predicting user's utilities with Machine Learning techniques for Computational Persuasion
ostlog is a self-tracking tool that motivates individual care, health and well-being.
Code and accompanying documentation within this repository focuses on curation of intensive longitudinal data (ILD) from EMA questionnaires from both pre- and post- quit periods; other data collected during the conduct of the study are beyond the scope of this repository and accompanying documentation.
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