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Analysis of the impact of adherent perirenal fat on peri-operative outcomes of robotic partial nephrectomy.

World journal of urology
INTRODUCTION: Adherent perirenal fat (APF) can be defined as inflammatory fat sticking to renal parenchyma, whose dissection is difficult and makes it troublesome to expose the tumour. Our objective was to evaluate the impact of APF on the technical ...

Artificial neural network and falls in community-dwellers: a new approach to identify the risk of recurrent falling?

Journal of the American Medical Directors Association
BACKGROUND: Identification of the risk of recurrent falls is complex in older adults. The aim of this study was to examine the efficiency of 3 artificial neural networks (ANNs: multilayer perceptron [MLP], modified MLP, and neuroevolution of augmenti...

Prediction of biochemical recurrence after robot-assisted radical prostatectomy: analysis of 784 Japanese patients.

International journal of urology : official journal of the Japanese Urological Association
OBJECTIVES: To examine biochemical recurrence after robot-assisted radical prostatectomy in Japanese patients, and to develop a risk stratification model for biochemical recurrence.

Accuracy of Machine Learning Models to Predict In-hospital Cardiac Arrest: A Systematic Review.

Clinical nurse specialist CNS
PURPOSE/AIMS: Despite advances in healthcare, the incidence of in-hospital cardiac arrest (IHCA) has continued to rise for the past decade. Identifying those patients at risk has proven challenging. Our objective was to conduct a systematic review of...

An artificial intelligence-based gout management system reduced chronic kidney disease incident and improved target serum urate achievement.

Rheumatology (Oxford, England)
OBJECTIVES: Stage ≥3 chronic kidney disease (CKD) affects ∼25% of people with gout. The effects of urate-lowering therapy (ULT) on CKD incidence and progression have remained inconclusive. Here, we assessed the impact of a gout ULT clinic interventio...

Prediction of hypertension and diabetes in twin pregnancy using machine learning model based on characteristics at first prenatal visit: national registry study.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
OBJECTIVE: To develop a prediction model for hypertensive disorders of pregnancy (HDP) and gestational diabetes mellitus (GDM) in twin pregnancy using characteristics obtained at the first prenatal visit.

Epidemiology characteristics and clinical outcomes of composite Hodgkin lymphoma and diffuse large B-cell lymphoma using machine learning.

The oncologist
Composite lymphoma (CL) is rare. We conducted an analysis of 53 329 cases of diffuse large B-cell lymphoma (DLBCL), 17,916 cases of Hodgkin lymphoma (HL), and 869 cases of composite HL and DLBCL from the SEER database diagnosed between 2000 and 2019....

Risk evaluation and incidence prediction of endolymphatic hydrops using multilayer perceptron in patients with audiovestibular symptoms.

Medicine
Endolymphatic hydrops (EH) has been visualized on magnetic resonance imaging (MRI) in patients with various inner ear diseases. The purpose of this study was to evaluate the prevalence and risk factors of significant EH on inner ear MRI in patients w...

A deep-learning retinal aging biomarker for cognitive decline and incident dementia.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: The utility of retinal photography-derived aging biomarkers for predicting cognitive decline remains under-explored.