Application of Low-Cost, Easy-to-Use, Portable Biosensor Systems for Diagnosing Bladder Dysfunctions

Myung, Nosang V.; Jung, Sungyong; Kim, Jayoung

doi:10.5213/inj.1938020.010

Cited by 8 publications

(8 citation statements)

References 5 publications

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“…We agree with the excellent viewpoints of Myung et al [5] that emphasize the importance of research and development of small, diverse, accurate, and multifunctional sensors to accomplish preventative, early diagnostic, and patient-specific treatment. But development in this regard is required in a wide range of fields, and each field requires multidisciplinary development of biological, chemical, physical, physiologic, electrical, and nanoscience technologies.…”

Section: Application Of Smart Healthcaresupporting

confidence: 91%

“…We completely agree with the opinion that development related to mobile health devices can be a game changer in smart healthcare and in the future healthcare industry [5]. For this to happen, the debate over the issue of invasion of privacy must be addressed and this problem should be resolved.…”

Section: Addendummentioning

confidence: 54%

“…Such integration can provide customized healthcare services without time and space limitations [1]. It is encouraging to look at a series of smart healthcare related studies—such as Dakurah et al [2], Lee et al [3], Kang et al [4], and Myung et al [5]—published in the International Neurourology Journal (INJ), a rising journal in the medical science field, dealing with such technology. In order to become a leader in this field, we believe that it is essential to address smart healthcare, and by adding our views on such technology, we wish to join this discussion.…”

Section: Overview Of Smart Healthcarementioning

confidence: 99%

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The Prospect of a New Smart Healthcare System: A Wearable Device-Based Complex Structure of Position Detecting and Location Recognition System

et al. 2019

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Smart healthcare is the integration of high technology-such as artificial intelligence (AI), big data, Internet of Things (IoT), cloud, and Nano technology-with medical healthcare. Such integration can provide customized healthcare services without time and space limitations [1]. It is encouraging to look at a series of smart healthcare related studies-such as Dakurah et al. [2], Lee et al. [3], Kang et al. [4], and Myung et al. [5]-published in the International Neurourology Journal (INJ), a rising journal in the medical science field, dealing with such technology. In order to become a leader in this field, we believe that it is essential to address smart healthcare, and by adding our views on such technology, we wish to join this discussion. The upcoming fourth industrial revolution will have an extensive and comprehensive impact, complexly affecting all areas of medicine. However, in reality, the direction of the development and utilization of technology in each area is not yet clear. There is still continuous development, therefore, planning and realization for the future must be done through human imagi

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Section: Application Of Smart Healthcaresupporting

confidence: 91%

Section: Addendummentioning

confidence: 54%

Section: Overview Of Smart Healthcarementioning

confidence: 99%

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The Prospect of a New Smart Healthcare System: A Wearable Device-Based Complex Structure of Position Detecting and Location Recognition System

et al. 2019

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“…The possibility of AI in medicine has been widely theorized over the past decades ( Chung et al, 2019 ; Myung et al, 2019 ). Reproductive urology is a subfield where AI can contribute greatly because it has several limitations in the current predictive model and subjectivity within the field.…”

Section: Application Of Artificial Intelligence In Urological Settingmentioning

confidence: 99%

Applications of artificial intelligence in urological setting: a hopeful path to improved care

Eun¹,

Kim²,

Kim³

2021

J Exerc Rehabil

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Artificial intelligence (AI) has been introduced in urology research and practice. Application of AI leads to better accuracy of disease diagnosis and predictive model for monitoring of responses to medical treatments. This mini-review article aims to summarize current applications and development of AI in urology setting, in particular for diagnosis and treatment of urological diseases. This review will introduce that machine learning algorithm-based models will enhance the prediction accuracy for various bladder diseases including interstitial cystitis, bladder cancer, and reproductive urology.

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“…Biosensors consist of a modified metal electrode as a transducer, biological components as a bioreceptor, and the electronic system [7]. Therefore, this method as a cost-effective [8][9][10][11], sensitive, selective, reproducibility and stability technique provides a diagnostic tool to sense biological analyses with a wide range [10,12].…”

Section: Introductionmentioning

confidence: 99%

Comparison between various biosensor methods for human T-lymphotropic virus-1 (HTLV-1) detection

Kamali

Zandi

Ghasemzadeh‐Moghaddam

et al. 2021

Mol Biol Rep

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Due to the drawback of traditional and current diagnostic methods including serological and molecular assays, the development of the rapid and free-PCR techniques can be an alternative technique for the human T-cell lymphotropic virus (HTLV-1) DNA detection sequences. On the other hand, early detection of HTLV-1 prevents two dangerous diseases including Adult T-cell leukemia/lymphoma and HTLV-1 Associated Myelopathy/Tropical Spastic Paraparesis. The biosensor-based methods are sensitive techniques that can provide new opportunities to detect infectious diseases, particularly in the early stage. This study provides a comparative view among recently designed biosensors for the detection of HTLV-1.

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Application of Low-Cost, Easy-to-Use, Portable Biosensor Systems for Diagnosing Bladder Dysfunctions

Cited by 8 publications

References 5 publications

The Prospect of a New Smart Healthcare System: A Wearable Device-Based Complex Structure of Position Detecting and Location Recognition System

The Prospect of a New Smart Healthcare System: A Wearable Device-Based Complex Structure of Position Detecting and Location Recognition System

Applications of artificial intelligence in urological setting: a hopeful path to improved care

Comparison between various biosensor methods for human T-lymphotropic virus-1 (HTLV-1) detection

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