AIMC Topic: Aged

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Comparative Analysis of the Diagnostic Value of S-Detect Technology in Different Planes Versus the BI-RADS Classification for Breast Lesions.

Academic radiology
RATIONALE AND OBJECTIVES: S-Detect, a deep learning-based Computer-Aided Detection system, is recognized as an important tool for diagnosing breast lesions using ultrasound imaging. However, it may exhibit inconsistent findings across multiple imagin...

Deep learning radiomics based on ultrasound images for the assisted diagnosis of chronic kidney disease.

Nephrology (Carlton, Vic.)
AIM: This study aimed to explore the value of ultrasound (US) images in chronic kidney disease (CKD) screening by constructing a CKD screening model based on grey-scale US images.

High-Throughput Deep Learning Detection of Mitral Regurgitation.

Circulation
BACKGROUND: Diagnosis of mitral regurgitation (MR) requires careful evaluation by echocardiography with Doppler imaging. This study presents the development and validation of a fully automated deep learning pipeline for identifying apical 4-chamber v...

Prediction of neurologic outcome after out-of-hospital cardiac arrest: An interpretable approach with machine learning.

Resuscitation
UNLABELLED: Out-of-hospital cardiac arrest (OHCA) is a critical condition with low survival rates. In patients with a return of spontaneous circulation, brain injury is a leading cause of death. In this study, we propose an interpretable machine lear...

Assessment of EMR ML Mining Methods for Measuring Association between Metal Mixture and Mortality for Hypertension.

High blood pressure & cardiovascular prevention : the official journal of the Italian Society of Hypertension
INTRODUCTION: There are limited data available regarding the connection between heavy metal exposure and mortality among hypertension patients.

Machine Learning and Deep Learning Approaches in Lifespan Brain Age Prediction: A Comprehensive Review.

Tomography (Ann Arbor, Mich.)
The concept of 'brain age', derived from neuroimaging data, serves as a crucial biomarker reflecting cognitive vitality and neurodegenerative trajectories. In the past decade, machine learning (ML) and deep learning (DL) integration has transformed t...

Feedback control of heart rate during robotics-assisted tilt table exercise in patients after stroke: a clinical feasibility study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Patients with neurological disorders including stroke use rehabilitation to improve cognitive abilities, to regain motor function and to reduce the risk of further complications. Robotics-assisted tilt table technology has been developed ...

Age prediction from 12-lead electrocardiograms using deep learning: a comparison of four models on a contemporary, freely available dataset.

Physiological measurement
The 12-lead electrocardiogram (ECG) is routine in clinical use and deep learning approaches have been shown to have the identify features not immediately apparent to human interpreters including age and sex. Several models have been published but no ...

Coagulation Risk Predicting in Anticoagulant-Free Continuous Renal Replacement Therapy.

Blood purification
INTRODUCTION: Continuous renal replacement therapy (CRRT) is a prolonged continuous extracorporeal blood purification therapy to replace impaired renal function. Typically, CRRT therapy requires routine anticoagulation, but for patients at risk of bl...

Detection and position evaluation of chest percutaneous drainage catheter on chest radiographs using deep learning.

PloS one
PURPOSE: This study aimed to develop an algorithm for the automatic detecting chest percutaneous catheter drainage (PCD) and evaluating catheter positions on chest radiographs using deep learning.