The Current State of Artificial Intelligence Application in Urology
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Artificial intelligence (AI) is being used in many areas of healthcare, including disease diagnosis and personalized treatment and rehabilitation management. Medical AI research and development has primarily focused on diagnosis, prediction, treatment, and management as an aid to patient care. AI is being utilized primarily in the areas of personal healthcare and diagnostic imaging. In the field of urology, significant investments are being made in the development of urination monitoring systems in the field of personal healthcare and ureteral stricture and urinary stone diagnosis solutions in the field of diagnostic imaging. In addition, AI technology is also being applied in the field of neurogenic bladder to develop risk monitoring systems based on video and audio data. This paper examines the application of AI to urological diseases and discusses the current trends and future prospects of AI research.
Abstract
Artificial intelligence (AI) is being used in many areas of healthcare, including disease diagnosis and personalized treatment and rehabilitation management. Medical AI research and development has primarily focused on diagnosis, prediction, treatment, and management as an aid to patient care. AI is being utilized primarily in the areas of personal healthcare and diagnostic imaging. In the field of urology, significant investments are being made in the development of urination monitoring systems in the field of personal healthcare and ureteral stricture and urinary stone diagnosis solutions in the field of diagnostic imaging. In addition, AI technology is also being applied in the field of neurogenic bladder to develop risk monitoring systems based on video and audio data. This paper examines the application of AI to urological diseases and discusses the current trends and future prospects of AI research.
참고문헌 (21)
- Park SH, "Building a new culture for quality management in the era of the Fourth Industrial Revolution", Total Qual Manag Bus Excell, 28, pp.934~945 (2017)
- Konstantinos-Vaios Mytilekas, "Defining Voiding Dysfunction in Women: Bladder Outflow Obstruction Versus Detrusor Underactivity", International Neurourology Journal, 25(3), pp.244~251 (2021), 대한배뇨장애요실금학회[DOI]
- 유지웅, "Comparison of Efficacy of Different Surgical Techniques for Benign Prostatic Obstruction", International Neurourology Journal, 25(3), pp.252~262 (2021), 대한배뇨장애요실금학회[DOI]
- 김현우, "Pathophysiology and Management of Long-term Complications After Transvaginal Urethral Diverticulectomy", International Neurourology Journal, 25(3), pp.202~209 (2021), 대한배뇨장애요실금학회[DOI]
- 장은비, "Catheter-Related Bladder Discomfort: How Can We Manage It?", International Neurourology Journal, 24(4), pp.324~331 (2020), 대한배뇨장애요실금학회[DOI]
- 권휘안, "Lower Urinary Tract Symptoms in Prostate Cancer Patients Treated With Radiation Therapy: Past and Present", International Neurourology Journal, 25(2), pp.119~127 (2021), 대한배뇨장애요실금학회[DOI]
- Aykut Baser, "Is There a Correlation Between Behçet Disease and Lower Urinary Tract Symptoms?", International Neurourology Journal, 24(2), pp.150~155 (2020), 대한배뇨장애요실금학회[DOI]
- 김수진, "Diagnostic Value of the Maximum Urethral Closing Pressure in Women With Overactive Bladder Symptoms and Functional Bladder Outlet Obstruction", International Neurourology Journal, 26, pp.1~7 (2022), 대한배뇨장애요실금학회[DOI]
- 황보택근, "Personalized Urination Activity Recognition Based on a Recurrent Neural Network Using Smart Band", International Neurourology Journal, 22, pp.91~100 (2018), 대한배뇨장애요실금학회
- 은성종, "Personalized Urination Activity Management Based on an Intelligent System Using a Wearable Device", International Neurourology Journal, 25(3), pp.229~235 (2021), 대한배뇨장애요실금학회[DOI]
- 은성종, "Development of an Artificial Intelligence-Based Support Technology for Urethral and Ureteral Stricture Surgery", International Neurourology Journal, 26(1), pp.78~84 (2022), 대한배뇨장애요실금학회[DOI]
- Wen L, "A negative correlation ensemble transfer learning method for fault diagnosis based on convolutional neural network", Math Biosci Eng, 16, pp.3311~3330 (2019)
- 김진욱, "Past, Present, and Future in the Study of Neural Control of the Lower Urinary Tract", International Neurourology Journal, 24(3), pp.191~199 (2020), 대한배뇨장애요실금학회[DOI]
- Koonce B, "Convolutional neural networks with swift for tensorflow", pp.63~72 (2021), Apress
- Quach LD, "Using SURF to improve Resnet-50 model for poultry disease recognition algorithm", 2020 International Conference on Computational Intelligence (ICCI) (2020), IEEE
- Miranda ND, "Convolutional neural network pada klasifikasi sidik jari menggunakan RESNET-50", J Tek Inform(JUTIF), 1, pp.61~68 (2020)
- 은성종, "A Study on the Optimal Artificial Intelligence Model for Determination of Urolithiasis", International Neurourology Journal, 26(3), pp.210~218 (2022), 대한배뇨장애요실금학회[DOI]
- Özcan F, "The relationship between urinary symptom severity and functional status in patients with stroke", Scott Med J, 67, pp.64~70 (2022)
- Musco S, "Prevalence of nocturia after brain injury : a cross-sectional study in a single rehabilitation center", Brain Inj, 35, pp.90~95 (2021)
- 김의선, "Development of Early-Stage Stroke Diagnosis System for the Elderly Neurogenic Bladder Prevention", International Neurourology Journal, 26, pp.76~82 (2022), 대한배뇨장애요실금학회[DOI]
- 김의선, "Artificial Intelligence-Based Speech Analysis System for Medical Support", International Neurourology Journal, 27(2), pp.99~105 (2023), 대한배뇨장애요실금학회[DOI]