Applications of Microwaves in Medicine Leveraging Artificial Intelligence: Future Perspectives

Gopalakrishnan, Keerthy; Adhikari, Aakriti; Pallipamu, Namratha; Singh, Mansunderbir; Nusrat, Tasin; Gaddam, Sunil; Samaddar, Poulami; Rajagopal, Anjali; Cherukuri, Akhila Sai Sree; Yadav, Anmol; Manga, Shreya Sai; Damani, Devanshi N.; Shivaram, Suganti; Dey, Shuvashis; Roy, Sayan; Mitra, Dipankar; Arunachalam, Shivaram P.

doi:10.3390/electronics12051101

Cited by 13 publications

(7 citation statements)

References 183 publications

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“…MWI uses electromagnetic waves at frequencies ranging from 0.5 GHz to 9.0 GHz to detect dielectric contrast that scatters from the tissue of the imaging domain [ 104 ]. Microwave (MW) technology can potentially help diagnose malignant tumors and other pathologies using the evaluation of complex permittivity of the tissue [ 105 , 106 ]. MW are safe diagnostic tools that generate images based on differences in dielectric properties.…”

Section: Discussionmentioning

confidence: 99%

Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging

Sethi

Muddaloor

Anvekar

et al. 2023

Sensors

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Respiratory disorders, being one of the leading causes of disability worldwide, account for constant evolution in management technologies, resulting in the incorporation of artificial intelligence (AI) in the recording and analysis of lung sounds to aid diagnosis in clinical pulmonology practice. Although lung sound auscultation is a common clinical practice, its use in diagnosis is limited due to its high variability and subjectivity. We review the origin of lung sounds, various auscultation and processing methods over the years and their clinical applications to understand the potential for a lung sound auscultation and analysis device. Respiratory sounds result from the intra-pulmonary collision of molecules contained in the air, leading to turbulent flow and subsequent sound production. These sounds have been recorded via an electronic stethoscope and analyzed using back-propagation neural networks, wavelet transform models, Gaussian mixture models and recently with machine learning and deep learning models with possible use in asthma, COVID-19, asbestosis and interstitial lung disease. The purpose of this review was to summarize lung sound physiology, recording technologies and diagnostics methods using AI for digital pulmonology practice. Future research and development in recording and analyzing respiratory sounds in real time could revolutionize clinical practice for both the patients and the healthcare personnel.

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Section: Discussionmentioning

confidence: 99%

Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging

Sethi

Muddaloor

Anvekar

et al. 2023

Sensors

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“…Microwaves benefit from integrating AI algorithms and techniques as AI enables advanced data processing, image reconstruction, and analysis 93,94 . This integration enhances the accuracy and efficiency of MWI in healthcare applications by leveraging AI 95 .…”

Section: Artificial Intelligence Assistance In Mwi: Techniques and He...mentioning

confidence: 99%

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

Khalid,

Zubair,

Mehmood

et al. 2024

npj Imaging

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In recent years, microwave imaging (MWI) has emerged as a non-ionizing and cost-effective modality in healthcare, specifically within medical imaging. Concurrently, advances in artificial intelligence (AI) have significantly augmented the capabilities of medical imaging tools. This paper explores the intersection of these two domains, focusing on the integration of AI algorithms into MWI techniques to elevate accuracy and overall performance. Within the scope of existing literature, representative prior works are compared concerning the application of AI in both the “MWI for Healthcare Applications" and “Artificial Intelligence Assistance In MWI" sections. This comparative analysis sheds light on the diverse approaches employed to enhance the synergy between AI and MWI. While highlighting the state-of-the-art technology in MWI and its historical context, this paper delves into the historical taxonomy of AI-assisted MWI, elucidating the evolution of intelligent systems within this domain. Moreover, it critically examines prominent works, providing a nuanced understanding of the advancements and challenges encountered. Addressing the limitations and challenges inherent in developing AI-assisted MWI systems like Generalization to different conditions, Generalization to different conditions, etc the paper offers a brief synopsis of these obstacles, emphasizing the importance of overcoming them for robust and reliable results in actual clinical environments. Finally, the paper not only underscores the current advancements but also anticipates future innovations and developments in utilizing AI for MWI applications in healthcare.

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“…Artificial Intelligence can design automated different antenna configurations for wearable devices. There are different algorithms, such as neural networks, and genetic algorithms, to analyze complex data sets to make the antenna design more effective for health monitoring systems such as microwave imaging, and ablation [55]. These algorithms can improve the adaptability of wearable antennas in the case of reconfigurable antennas and also for designing biomedical sensors.…”

Section: Figure 3 Monopole Antenna With Electromagnetic Bandgap Struc...mentioning

confidence: 99%

Recent Advancements in Modern Antenna Design for Wearable Devices

Shawan¹,

Kawser²,

Zohra³

et al. 2023

JAIMLNN

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The rapid growth of wearable technologies within wireless body area networks (WBANs) has increased the demand for advanced wearable antennas. The human body's presence creates significant challenges for these antennas since it behaves differently as a wave propagation medium. It is necessary to prioritize specific requirements for antenna design, such as size, frequency, efficiency, wideband and multiband operation, because of body interaction and signal attenuation. The development of novel methodologies, the use of state-of-the-art fabrication methods, and the advancement of antenna designs have been the main areas of attention for researchers in this field in recent years. This research investigates contemporary advancements in wearable antennas, particularly emphasizing utilizing recent materials, fabrication processes, and new techniques. It also highlights the unique applicability of these antennas in advanced WBAN systems.

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Applications of Microwaves in Medicine Leveraging Artificial Intelligence: Future Perspectives

Cited by 13 publications

References 183 publications

Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging

Digital Pulmonology Practice with Phonopulmography Leveraging Artificial Intelligence: Future Perspectives Using Dual Microwave Acoustic Sensing and Imaging

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

Recent Advancements in Modern Antenna Design for Wearable Devices

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