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Urinalysis

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A Novel Machine-Learning Algorithm to Predict Stone Recurrence with 24-Hour Urine Data.

Journal of endourology
The absence of predictive markers for kidney stone recurrence poses a challenge for the clinical management of stone disease. The unpredictability of stone events is also a significant limitation for clinical trials, where many patients must be enro...

Renal Cell Carcinoma Discrimination through Attenuated Total Reflection Fourier Transform Infrared Spectroscopy of Dried Human Urine and Machine Learning Techniques.

International journal of molecular sciences
Renal cell carcinoma (RCC) is the sixth most common cancer in men and is often asymptomatic, leading to incidental detection in advanced disease stages that are associated with aggressive histology and poorer outcomes. Various cancer biomarkers are f...

Predictive performance of urinalysis for urine culture results according to causative microorganisms: an integrated analysis with artificial intelligence.

Journal of clinical microbiology
Urinary tract infections (UTIs) are pervasive and prevalent in both community and hospital settings. Recent trends in the changes of the causative microorganisms in these infections could affect the effectiveness of urinalysis (UA). We aimed to evalu...

Urine Analysed by FTIR, Chemometrics and Machine Learning Methods in Determination Spectroscopy MarkerĀ of Prostate Cancer in Urine.

Journal of biophotonics
Prostate-specific antigen (PSA) is the most commonly used marker of prostate cancer. However, nearly 25% of men with elevated PSA levels do not have cancer and nearly 20% of patients with prostate cancer have normal serum PSA levels. Therefore, in th...

Artificial Intelligence in Diagnostics: Enhancing Urine Test Accuracy Using a Mobile Phone-Based Reading System.

Annals of laboratory medicine
BACKGROUND: Urinalysis, an essential diagnostic tool, faces challenges in terms of standardization and accuracy. The use of artificial intelligence (AI) with mobile technology can potentially solve these challenges. Therefore, we investigated the eff...

"Three-in-one" Analysis of Proteinuria for Disease Diagnosis through Multifunctional Nanoparticles and Machine Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Urinalysis is one of the predominant tools for clinical testing owing to the abundant composition, sufficient volume, and non-invasive acquisition of urine. As a critical component of routine urinalysis, urine protein testing measures the levels and ...

Diagnosis of Chronic Kidney Disease Using Retinal Imaging and Urine Dipstick Data: Multimodal Deep Learning Approach.

JMIR medical informatics
BACKGROUND: Chronic kidney disease (CKD) is a prevalent condition with significant global health implications. Early detection and management are critical to prevent disease progression and complications. Deep learning (DL) models using retinal image...

ML-UrineQuant: A machine learning program for identifying and quantifying mouse urine on absorbent paper.

Physiological reports
The void spot assay has gained popularity as a way of assessing functional bladder voiding parameters in mice, but analyzing the size and distribution of urine spot patterns on filter paper with software remains problematic due to inter-laboratory di...

Label-free urinary protein detection through machine learning analysis of single droplet evaporation patterns.

Analytica chimica acta
BACKGROUND: Chronic kidney disease (CKD) is a major global public health issue, with a steadily increasing incidence. Urinary protein detection serves as a crucial indicator for the diagnosis, monitoring and management of CKD. However, current method...

Will artificial intelligence (AI) replace cytopathologists: a scoping review of current applications and evidence of A.I. in urine cytology.

World journal of urology
PURPOSE: Urine cytology, while valuable in facilitating the detection and surveillance of bladder cancer, has notable limitations. The application of artificial intelligence (AI) in urine cytology holds significant promise for improving diagnostic ac...