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Hydra, a Computer-Based Platform for Aiding Clinicians in Cardiovascular Analysis and Diagnosis

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Connected-Health Algorithm: Development and Evaluation.

Elena Vlahu-Gjorgievska¹, Saso Koceski², Igor Kulev³

¹Faculty of Information and Communication Technologies, University "St. Kliment Ohridski", Bitola, Republic of Macedonia. elena.vlahu@fikt.edu.mk.

Journal of Medical Systems

|February 29, 2016

Summary

This summary is machine-generated.

This study introduces a connected health algorithm using social computing to recommend physical activities for improved health. The algorithm successfully identified effective activities, aiding users in weight loss goals.

Keywords:

Collaborative algorithms Connected health Healthcare information system Recommendations e-Health

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Area of Science:

Digital Health
Health Informatics
Social Computing

Background:

Growing interest in Information and Communication Technology (ICT) for medical monitoring and personal healthcare.
Need for personalized health recommendations based on individual and community data.
Leveraging social computing principles for health interventions.

Purpose of the Study:

To design and propose a connected health algorithm inspired by social computing.
To provide personalized activity recommendations for health improvement.
To increase user confidence in selecting beneficial physical activities.

Main Methods:

Development of a connected health algorithm utilizing a social computing paradigm.
Algorithm incorporates user's health condition and historical data from similar users.
Experimental validation using real-world data from 1000 active users.

Main Results:

The algorithm's recommended physical activities for weight loss (≥0.5 kg) appeared in the top half of the recommendation list.
High probability (>0.6) of successful recommendations at a 1% significance level.
Demonstrated effectiveness of the social computing-inspired algorithm in a real-world setting.

Conclusions:

The proposed connected health algorithm effectively recommends physical activities for health improvement.
Social computing paradigm offers a viable approach for personalized digital health solutions.
The algorithm shows promise in supporting user-driven health management and weight loss efforts.