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Copyright ©The Author(s) 2025. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Crit Care Med. Dec 9, 2025; 14(4): 104703
Published online Dec 9, 2025. doi: 10.5492/wjccm.v14.i4.104703
Preventing diagnostic errors in critical care using millimeter-wave technology: A transformative approach to patient safety
Andreas G Siamarou
Andreas G Siamarou, Department of Computer Science, Ledra College, Nicosia 2012, Cyprus
Author contributions: Siamarou AG completed all the work alone.
Institutional review board statement: The study was reviewed and approved by Ledra College, Nicosia, Cyprus, review board.
Informed consent statement: There were no participants on this study.
Conflict-of-interest statement: The author declares that they have no conflict of interest to disclose.
STROBE statement: The authors have read the STROBE Statement – checklist of items, and the manuscript was prepared and revised according to the STROBE Statement – checklist of items.
Data sharing statement: No additional data are available.
Open Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Noncommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Andreas G Siamarou, Department of Computer Science, Ledra College, Nicosia, Athalassas Ave 60, Strovolos 2012, Cyprus. siamarou.andreas@gmail.com
Received: December 31, 2024
Revised: April 24, 2025
Accepted: August 20, 2025
Published online: December 9, 2025
Processing time: 334 Days and 20 Hours
Abstract
BACKGROUND

Diagnostic errors in critical care settings are a significant challenge, often leading to adverse patient outcomes and increased healthcare costs. Millimeter-wave (mmWave) technology, with its ability to provide high-resolution, real-time data, offers a transformative solution to enhance diagnostic accuracy and patient safety. This paper explores the integration of mmWave technology in intensive care units (ICUs) to enable non-invasive monitoring, minimize diagnostic errors, and improve clinical decision-making. By addressing key challenges, including data latency, signal interference, and implementation feasibility, this approach has the potential to revolutionize patient monitoring systems and set a new standard for critical care delivery. The paper discusses the high prevalence of diagnostic errors in medical care, particularly in primary care and ICUs, and emphasizes the need for improvement in diagnostic accuracy. Diagnostic errors are responsible for a significant number of deaths, disabilities, prolonged hospitalizations and delays in diagnosis worldwide.

AIM

To address this issue, the paper proposes the use of ultrafast wireless medical big data transmission in primary care, specifically in remote smart sensors monitoring devices. It suggests that wireless transmission with a speed up to 100 Gb/s (12.5 Gbytes/s) within a short distance (1-10 meters) is necessary to reduce diagnostic errors.

METHODS

The method used in the study, includes system design and testing a channel sounder operating at 63.4-64.4 GHz frequency range. The system demonstrated dynamic range of 70 dB, noise level of -110 dBm, and a time resolution of 1 ns. The experiment measured the impulse response of the channel in 36 locations within the primary care/ICU scenario.

RESULTS

The system was tested in a simulated ICU environment to evaluate the Latency: Assessing the time delay in data transmission and processing. The results of the study showed that the system met the requirements of ICUs, providing excellent latency values. The delay spread and excess delay values were within acceptable limits, indicating successful resolution of ICU requirements. The paper suggests timely deployment of such a system. Impact on data transmission: A 100 MB magnetic resonance imaging scan can be transmitted in approximately 0.008 seconds; A 1 GB scan would take approximately 0.08 seconds; This capability could revolutionize healthcare, enabling real-time remote diagnostics and comparisons with artificial Intelligence models, even in large-scale systems.

CONCLUSION

The experiment demonstrated the feasibility of using high-speed wireless transmission for improved diagnostics in ICUs, offering potential benefits in terms of reduced errors and improved patient outcomes. The findings are deemed valuable to the medical community and public healthcare systems, and it is suggested further research in this area.

Keywords: Big data; Primary care; Diagnostics errors; Smart health; Internet of medical things; mm wave technology; Intensive care unit; Remote sensors; Consultation; Vital signs; Radiology; Telemetry

Core Tip: Millimeter-wave technology offers a transformative approach to preventing diagnostic errors in critical care. By providing precise, non-invasive, and real-time monitoring, this innovation enhances patient safety and supports better clinical outcomes. Future research should focus on refining the technology, addressing implementation challenges, and exploring its potential across diverse healthcare environments. We anticipated that our study to be a starting point for more sophisticated research in detecting and preventing diagnostics errors in primary care along with artificial intelligence, machine learning, internet of things and high computation in terms of mm-Wave wireless transmission.