AIMC Topic: Urine
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Evaluation of an artificial intelligence algorithm for assisting the Paris System in reporting urinary cytology: A pilot study.
Cancer cytopathology
Jun 21, 2022
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...
A Calibrated Multiexit Neural Network for Detecting Urothelial Cancer Cells.
Computational and mathematical methods in medicine
Jun 13, 2021
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
May 12, 2021
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...
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
Oct 7, 2020
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...
Developing a Machine Learning Algorithm for Identifying Abnormal Urothelial Cells: A Feasibility Study.
Acta cytologica
Oct 6, 2020
INTRODUCTION: Urine cytology plays an important role in diagnosing urothelial carcinoma (UC). However, urine cytology interpretation is subjective and difficult. Morphogo (ALAB, Boston, MA, USA), equipped with automatic acquisition and scanning, opti...
Middle Aged
Diagnosis, Computer-Assisted
Urologic Neoplasms
Predictive Value of Tests
Aged
Aged, 80 and over
Male
Image Interpretation, Computer-Assisted
Urine
Proof of Concept Study
Urothelium
Prostatic Neoplasms
Carcinoma
Feasibility Studies
Cytodiagnosis
Humans
Neural Networks, Computer
Machine Learning
Female
Reproducibility of Results
Sensor-Array Optimization Based on Time-Series Data Analytics for Sanitation-Related Malodor Detection.
IEEE transactions on biomedical circuits and systems
Jun 12, 2020
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...
Generic Isolated Cell Image Generator.
Cytometry. Part A : the journal of the International Society for Analytical Cytology
Oct 8, 2019
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...
Performance of an artificial intelligence algorithm for reporting urine cytopathology.
Cancer cytopathology
Aug 14, 2019
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...
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
Jun 21, 2019
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 ...
Determination of appropriate urine volume cutoff values for voided urine specimens to assess adequacy.
Journal of the American Society of Cytopathology
Nov 7, 2018
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...
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