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Urine

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Determination of appropriate urine volume cutoff values for voided urine specimens to assess adequacy.

Journal of the American Society of Cytopathology
INTRODUCTION: Incorporating urine volume into adequacy assessment was recommended by The Paris System for Reporting Urinary Cytology. The concept was relatively new, however, and supportive studies were sparse. We accordingly aimed to determine the r...

Artificial intelligence and machine learning for predicting acute kidney injury in severely burned patients: A proof of concept.

Burns : journal of the International Society for Burn Injuries
BACKGROUND: Burn critical care represents a high impact population that may benefit from artificial intelligence and machine learning (ML). Acute kidney injury (AKI) recognition in burn patients could be enhanced by ML. The goal of this study was to ...

Performance of an artificial intelligence algorithm for reporting urine cytopathology.

Cancer cytopathology
BACKGROUND: Unlike Papanicolaou tests, there are no commercially available computer-assisted automated screening systems for urine specimens. Despite The Paris System for Reporting Urinary Cytology, there still is poor interobserver agreement with ur...

Generic Isolated Cell Image Generator.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Building automated cancer screening systems based on image analysis is currently a hot topic in computer vision and medical imaging community. One of the biggest challenges of such systems, especially those using state-of-the-art deep learning techni...

Sensor-Array Optimization Based on Time-Series Data Analytics for Sanitation-Related Malodor Detection.

IEEE transactions on biomedical circuits and systems
There is an unmet need for a low-cost instrumented technology for detecting sanitation-related malodor as an alert for maintenance around shared toilets and emerging technologies for onsite waste treatment. In this article, our approach to an electro...

Use of artificial intelligence for tailored routine urine analyses.

Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
OBJECTIVES: Urine is the most common material tested in clinical microbiology laboratories. Automated analysis is already performed, permitting quicker results and decreasing the laboratory technologist's (LT) workload. These automatic systems have i...

A Calibrated Multiexit Neural Network for Detecting Urothelial Cancer Cells.

Computational and mathematical methods in medicine
Deep convolutional networks have become a powerful tool for medical imaging diagnostic. In pathology, most efforts have been focused in the subfield of histology, while cytopathology (which studies diagnostic tools at the cellular level) remains unde...

A deep learning system to diagnose the malignant potential of urothelial carcinoma cells in cytology specimens.

Cancer cytopathology
BACKGROUND: Although deep learning algorithms for clinical cytology have recently been developed, their application to practical assistance systems has not been achieved. In addition, whether deep learning systems (DLSs) can perform diagnoses that ca...

Evaluation of an artificial intelligence algorithm for assisting the Paris System in reporting urinary cytology: A pilot study.

Cancer cytopathology
BACKGROUND: The Paris System for Reporting Urinary Cytology (TPS) has been shown to improve bladder cancer diagnosis. Advances in artificial intelligence (AI) may assist and improve the clinical workflow by applying TPS in routine diagnostic services...