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Harnessing IoT for Proactive Cardiovascular Health: DEEP-CARDIO Recommender System

EasyChair Preprint no. 12937

7 pagesDate: April 6, 2024


DEEP-CARDIO Recommender System presents a proactive approach to cardiovascular health management, leveraging Internet of Things (IoT) technology to collect and analyze real-time physiological data. With cardiovascular diseases (CVDs) remaining a leading cause of mortality globally, preventive measures are crucial. DEEP-CARDIO integrates deep learning algorithms and predictive analytics to discern intricate patterns within the data, offering personalized risk assessments based on dynamic physiological markers such as heart rate variability and blood pressure trends. By providing tailored recommendations for lifestyle modifications and interventions, DEEP-CARDIO empowers individuals to mitigate their cardiovascular risk factors, while facilitating seamless communication between individuals and healthcare providers. With its scalability and accessibility, DEEP-CARDIO holds promise for improving public health outcomes by identifying high-risk individuals early and enabling targeted interventions to prevent adverse cardiovascular events.

Keyphrases: cardio, recommender, system

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
  author = {Julia Anderson and John Thomas},
  title = {Harnessing IoT for Proactive Cardiovascular Health: DEEP-CARDIO Recommender System},
  howpublished = {EasyChair Preprint no. 12937},

  year = {EasyChair, 2024}}
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