Prediction of chronic kidney disease using urinary dielectric properties and support vector machine

Mun, Peck Shen; Ting, Hua Nong; Mirhassani, Seyed Mostafa; Ong, Teng Aik; Wong, Chew Ming; Chong, Yip Boon

doi:10.1080/08327823.2016.1230927

Cited by 12 publications

(4 citation statements)

References 39 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In [29], the dielectric properties of urine samples from 40 healthy subjects were recorded across our frequency range of interest. The mean values from [29] are consistent with those of [15], [30]- [32]. Two other studies, [33] (2 healthy volunteers) and [34] (4 healthy volunteers) also reported urine properties within our frequency range of interest.…”

Section: B Selection Of Model Parameterssupporting

confidence: 85%

See 1 more Smart Citation

Proof-of-Concept of Microwave-Based Bladder State Detection Using Realistic Pelvic Models

Farshkaran¹,

Fry²,

Raterink

et al. 2024

IEEE Open J. Eng. Med. Biol.

View full text Add to dashboard Cite

Goal: Urinary incontinence (UI) affects a significant proportion of the population and is associated with negative physical and psychological side-effects. Microwave-based technologies may have the potential to monitor bladder volume, providing a proactive, low-cost and non-invasive tool to support individuals with UI. Methods: Studies to date on microwave bladder monitoring have been limited to highly simplified computational and experimental scenarios. In this work, we study the most realistic models to date (both male and female), which incorporate dielectrically and anatomically representative tissues of the pelvic region. Results: We examine the ability of detecting bladder fullness through both reflection and transmission-based parameters and, for the first time, study the effect of urine permittivity. As a proof-of-concept of bladder state detection, we further investigate reconstructing differential radar images of the bladder with two different volumes of urine. Conclusions: The results indicate that there is strong potential for monitoring and detecting the bladder state using microwave measurements.

show abstract

Section: B Selection Of Model Parameterssupporting

confidence: 85%

“… Measurements of the dielectric properties of human urine found in the literature. The mean values of (a) Relative permittivity and (b) conductivity are plotted at a temperature of 37 °C as reported in [29] , [30] , [31] , [32] , [33] , [34] . …”

Section: Methodsmentioning

confidence: 99%

Proof-of-Concept of Microwave-Based Bladder State Detection Using Realistic Pelvic Models

Farshkaran¹,

Fry²,

Raterink

et al. 2024

IEEE Open J. Eng. Med. Biol.

View full text Add to dashboard Cite

show abstract

“…Similar results were also shown when urine of diabetic and CKD patients was compared to normal subjects, but differences were more significant between normal and CKD patients [29]. Other studies have investigated the effect glycosuria on the dielectric properties of urine and observed an increase in dielectric constant with increasing glucose in urea [30,31,32,33]. All these studies demonstrate biomaterial dependency of urine dielectric properties.…”

Section: Discussionsupporting

confidence: 69%

“…Urea is one of the components that is degraded by the action of urease enzyme found in some infectious microorganism, breaking it into ammonia and carbon dioxide, thus raising the pH of urine up to 9 [36]. One study has shown that changes in the pH and ammonia concentration of fresh urine reach a steady state after 60-72 h [33]. Moreover, this change is accelerated at higher temperatures (e.g., 25 C and 30 C) [37].…”

Section: Discussionmentioning

confidence: 99%

Electrical detection of blood cells in urine

Nasir

Raji

Mustafa

et al. 2020

Heliyon

View full text Add to dashboard Cite

Available methods for detecting blood in the urine (hematuria) can be problematic since results can be influenced by many factors in patients and in the lab settings, resulting in false positive or false negative results. This necessitates the development of new, accurate and easy-access methods that save time and effort. This study demonstrates a label-free and accurate method for detecting the presence of red and white blood cells (RBCs and WBCs) in urine by measuring the changes in the dielectric properties of urine upon increasing concentrations of both cell types. The current method could detect changes in the electrical properties of fresh urine over a short time interval, making this method suitable for detecting changes that cannot be recognized by conventional methods. Correcting for these changes enabled the detection of a minimum cell concentration of 10 2 RBCs per ml which is not possible by conventional methods used in the labs except for the semi-quantitative method that can detect 50 RBCs per ml, but it is a lengthy and involved procedure, not suitable for high volume labs. This ability to detect very small amount of both types of cells makes the proposed technique an attractive tool for detecting hematuria, the presence of which is indicative of problems in the excretory system.

show abstract

Artificial Intelligence-Based Chronic Kidney Disease Prediction—A Review

Amaresh¹,

Sundaram²

2023

Lecture Notes in Networks and Systems

View full text Add to dashboard Cite

Prediction of chronic kidney disease using urinary dielectric properties and support vector machine

Cited by 12 publications

References 39 publications

Proof-of-Concept of Microwave-Based Bladder State Detection Using Realistic Pelvic Models

Proof-of-Concept of Microwave-Based Bladder State Detection Using Realistic Pelvic Models

Electrical detection of blood cells in urine

Artificial Intelligence-Based Chronic Kidney Disease Prediction—A Review

Contact Info

Product

Resources

About