IoT-enabled biosensors for real-time monitoring and early detection of chronic diseases

The integration of IoT-enabled biosensors approach to addressing global challenges posed by chronic diseases. This study highlights the potential of this convergence in healthcare by facilitating real-time monitoring, early detection, and personalized care. By surpassing limitations of traditional monitoring systems, IoT-enabled biosensors provide continuous insights into patients' health, enabling proactive interventions. Their applications are demonstrated in diverse domains, including remote monitoring, cardiac health, glucose management, and elderly care, showcasing their role in advancing precision medicine and improving patient outcomes. Despite technical hurdles, ongoing advancements in miniaturization, edge computing, and AI-driven analytics aim to enhance accuracy, efficiency, and ethical practices, paving the way for a proactive and patient-centric healthcare era.

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Publication Details

Journal
Physical Activity and Nutrition
Published
2024-12-31
DOI
https://doi.org/10.20463/pan.2024.0033
Citations
34
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
24.06

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article

IoT-enabled biosensors for real-time monitoring and early detection of chronic diseases

J.P. Park, J.H Kim, Jae Eun Lee, Hong-Seok Choi et al.
34 citations
Physical Activity and Nutrition
Artificial Intelligence in Healthcare
24.06
article

IoT-enabled biosensors for real-time monitoring and early detection of chronic diseases

J.P. Park, J.H Kim, Jae Eun Lee, Hong-Seok Choi, Md Najmul Hosain, Yi-Sub Kwak
article en
34 citations

Abstract

The integration of IoT-enabled biosensors approach to addressing global challenges posed by chronic diseases. This study highlights the potential of this convergence in healthcare by facilitating real-time monitoring, early detection, and personalized care. By surpassing limitations of traditional monitoring systems, IoT-enabled biosensors provide continuous insights into patients' health, enabling proactive interventions. Their applications are demonstrated in diverse domains, including remote monitoring, cardiac health, glucose management, and elderly care, showcasing their role in advancing precision medicine and improving patient outcomes. Despite technical hurdles, ongoing advancements in miniaturization, edge computing, and AI-driven analytics aim to enhance accuracy, efficiency, and ethical practices, paving the way for a proactive and patient-centric healthcare era.

Physical Activity and NutritionVol. 28(4)
Dong-Eui University (KR), University of Hawaii Maui College (US), Pukyong National University (KR)
Pukyong National University
Openalex Percentile: Top 0%
Artificial Intelligence in Healthcare
24.06
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