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Related Concept Videos

Issues And Trends In Healthcare Delivery System01:29

Issues And Trends In Healthcare Delivery System

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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Correction: Komatsu et al. Three-Dimensional Visualization and Detection of the Pulmonary Venous-Left Atrium Connection Using Artificial Intelligence in Fetal Cardiac Ultrasound Screening. <i>Bioengineering</i> 2026, <i>13</i>, 100.

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Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
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Artificial Intelligence-Driven Wireless Sensing for Health Management.

Merih Deniz Toruner1, Victoria Shi2, John Sollee1

  • 1The Warren Alpert Medical School, Brown University, Providence, RI 02903, USA.

Bioengineering (Basel, Switzerland)
|March 28, 2025
PubMed
Summary
This summary is machine-generated.

Wireless sensing combined with artificial intelligence (AI) offers powerful tools for real-time health monitoring and early disease detection. These AI-powered wireless sensing technologies are poised to enhance clinical care and precision medicine.

Keywords:
artificial intelligenceearly diagnosishealthcare monitoringwireless sensing

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Area of Science:

  • Biomedical Engineering
  • Medical Informatics
  • Artificial Intelligence in Medicine

Background:

  • Technological advancements enable the integration of wireless sensing and artificial intelligence (AI) for real-time medical monitoring and intervention.
  • Wireless sensing devices are increasingly applied in healthcare for early diagnosis, patient monitoring, and assessing treatment response.

Purpose of the Study:

  • To review the latest advancements in wireless sensing devices incorporating AI for clinical medicine.
  • To analyze the strengths and limitations of these technologies across various medical domains.
  • To identify future research directions in AI-powered wireless sensing for healthcare.

Main Methods:

  • A comprehensive literature search was conducted across PubMed, IEEEXplore, Embase, and Scopus.
  • 34 relevant articles focusing on real-world validation of wireless sensing were selected from 10,691 identified studies.
  • Analysis focused on clinical applications, strengths, limitations, and the value in precision medicine.

Main Results:

  • Wireless sensing and AI technologies show significant potential for improving diagnosis, treatment monitoring, and disease prevention.
  • Acoustic signals, channel state information, and radar are leading techniques for non-invasive physiological change detection.
  • The selected studies emphasize real-world validation and clinical applicability.

Conclusions:

  • Wireless sensing plays a crucial role in modern clinical care.
  • There is a growing trend towards integrating AI-powered wireless sensing into routine healthcare.
  • These technologies are expected to significantly support patient monitoring and diagnostic processes.