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Machine Learning-Based Pediatric Early Warning Score: Patient Outcomes in a Pre- Versus Post-Implementation Study, 2019-2023.

OBJECTIVES: To describe the deployment of pediatric Calculated Assessment of Risk and Triage (pCART)...

A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning.

Autonomous transportation systems have the potential to greatly impact the way we travel. A vital as...

GARNN: An interpretable graph attentive recurrent neural network for predicting blood glucose levels via multivariate time series.

Accurate prediction of future blood glucose (BG) levels can effectively improve BG management for pe...

Computer-aided cholelithiasis diagnosis using explainable convolutional neural network.

Accurate and precise identification of cholelithiasis is essential for saving the lives of millions ...

Identification of hub biomarkers in liver post-metabolic and bariatric surgery using comprehensive machine learning (experimental studies).

BACKGROUND: The global prevalence of non-alcoholic fatty liver disease (NAFLD) is approximately 30%,...

Using machine learning to predict outcomes following transcarotid artery revascularization.

Transcarotid artery revascularization (TCAR) is a relatively new and technically challenging procedu...

Radiogenomic explainable AI with neural ordinary differential equation for identifying post-SRS brain metastasis radionecrosis.

BACKGROUND: Stereotactic radiosurgery (SRS) is widely used for managing brain metastases (BMs), but ...

Advancing newborn care: Precise time of birth detection using ai-driven thermal imaging with adaptive normalization.

Around 5%-10% of newborns need assistance to start breathing. Currently, there is a lack of evidence...

Robot-Assisted Endodontic Retreatment: A Case Report with Clinical Considerations.

Fiber posts present significant challenges for nonsurgical endodontic retreatment, as improper remov...

Prognosis modelling of adverse events for post-PCI treated AMI patients based on inflammation and nutrition indexes.

OBJECTIVE: This study aimed to evaluate the predictive performance of inflammatory and nutritional i...

MCTASmRNA: A deep learning framework for alternative splicing events classification.

Alternative splicing (AS) plays crucial post-transcriptional gene function regulation roles in eukar...

Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions.

BACKGROUND: Post bariatric hypoglycaemic (PBH) is a late complication of weight loss surgery, charac...

Automated post-run analysis of arrayed quantitative PCR amplification curves using machine learning.

BACKGROUND: The TaqMan Array Card (TAC) is an arrayed, high-throughput qPCR platform that can simult...

Task-oriented robotic rehabilitation for back mobility and functioning in a post-intensive care unit obese patient: A case report.

BackgroundIntensive care unit (ICU) acquired weakness is a detrimental condition characterized by mu...

Assessing donor kidney function: the role of CIRBP in predicting delayed graft function post-transplant.

INTRODUCTION: Delayed graft function (DGF) shortens the survival time of transplanted kidneys and in...

Predicting work ability impairment in post COVID-19 patients: a machine learning model based on clinical parameters.

The Post COVID-19 condition (PCC) is a complex disease affecting health and everyday functioning. Th...

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