Academic Journal

Combined Use of Microwave Sensing Technologies and Artificial Intelligence for Biomedical Monitoring and Imaging.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Combined Use of Microwave Sensing Technologies and Artificial Intelligence for Biomedical Monitoring and Imaging.
Συγγραφείς: Martínez-Lozano, Andrea, Buitrago-Bernal, Alejandro, Roy, Langis, Vicente-Samper, José María, Juan, Carlos G.
Πηγή: Biosensors (2079-6374); Jan2026, Vol. 16 Issue 1, p67, 32p
Θεματικοί όροι: Microwave remote sensing, Artificial intelligence, Electronic data processing, Medical technology, Computer-assisted image analysis (Medicine), Patient monitoring, Biosensors, Medical equipment
Περίληψη: Microwave sensing technology is rapidly advancing and increasingly finding its way into biomedical applications, promising significant improvements for medical care. Concurrently, the rise of artificial intelligence (AI) is enabling significant enhancements in the biomedical domain. Close scrutiny of the recent literature reveals intense activity in both fields, with particularly impactful outcomes deriving from the combined use of advanced microwave techniques and AI for biomedical monitoring. In this review, an up-to-date compilation, from the perspective of the authors, of the most significant works published on these topics in recent years is given, focusing on their integration and current challenges. With the objective of analyzing the current landscape, we survey and compare state-of-the-art biosensors and imaging systems at all healthcare levels, from outpatient contexts to specialized medical equipment and laboratory analysis tools. We also delve into the relevant applications of AI in medicine for processing microwave-derived data. As our core focus, we analyze the synergistic integration of AI in the design of microwave devices and the processing of the acquired data, which have shown notable performances, opening new avenues for compact, affordable, and multi-functional medical devices. We conclude by synthesizing the prevailing technical, algorithmic, and translational challenges that must be addressed to realize this potential. [ABSTRACT FROM AUTHOR]
Copyright of Biosensors (2079-6374) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Complementary Index
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  Data: Combined Use of Microwave Sensing Technologies and Artificial Intelligence for Biomedical Monitoring and Imaging.
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  Data: Biosensors (2079-6374); Jan2026, Vol. 16 Issue 1, p67, 32p
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  Data: Microwave sensing technology is rapidly advancing and increasingly finding its way into biomedical applications, promising significant improvements for medical care. Concurrently, the rise of artificial intelligence (AI) is enabling significant enhancements in the biomedical domain. Close scrutiny of the recent literature reveals intense activity in both fields, with particularly impactful outcomes deriving from the combined use of advanced microwave techniques and AI for biomedical monitoring. In this review, an up-to-date compilation, from the perspective of the authors, of the most significant works published on these topics in recent years is given, focusing on their integration and current challenges. With the objective of analyzing the current landscape, we survey and compare state-of-the-art biosensors and imaging systems at all healthcare levels, from outpatient contexts to specialized medical equipment and laboratory analysis tools. We also delve into the relevant applications of AI in medicine for processing microwave-derived data. As our core focus, we analyze the synergistic integration of AI in the design of microwave devices and the processing of the acquired data, which have shown notable performances, opening new avenues for compact, affordable, and multi-functional medical devices. We conclude by synthesizing the prevailing technical, algorithmic, and translational challenges that must be addressed to realize this potential. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of Biosensors (2079-6374) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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              Text: Jan2026
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              Y: 2026
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