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A deep learning model for QRS delineation in organized rhythms during in-hospital cardiac arrest.

International journal of medical informatics
BACKGROUND: Cardiac arrest (CA) is the sudden cessation of heart function, typically resulting in loss of consciousness and cessation of pulse and breathing. The electrocardiogram (ECG) stands as an essential tool extensively utilized by clinicians, ...

A temporal-spatial feature fusion network for emotion recognition with individual differences reduction.

Neuroscience
PURPOSE: In the context of EEG-based emotion recognition tasks, a conventional strategy involves the extraction of spatial and temporal features, subsequently fused for emotion prediction. However, due to the pronounced individual variability in EEG ...

Predictive estimation of ovine hip joint centers: Neural networks vs. linear regression.

Journal of biomechanics
The purpose of this study was to investigate the utility of neural networks to estimate the hip joint center location in sheep and compare the accuracy of neural networks to previously developed linear regression models. CT scans from 16 sheep of var...

Super-resolution deep-learning reconstruction with 1024 matrix improves CT image quality for pancreatic ductal adenocarcinoma assessment.

European journal of radiology
OBJECTIVES: To evaluate the efficiency of super-resolution deep-learning reconstruction (SR-DLR) optimized for helical body imaging in assessing pancreatic ductal adenocarcinoma (PDAC) using normal-resolution (NR) CT scanner.

Cost-effectiveness of AI-based diabetic retinopathy screening in nationwide health checkups and diabetes management in Japan: A modeling study.

Diabetes research and clinical practice
AIMS: We evaluated the cost-effectiveness of artificial intelligence (AI)-based diabetic retinopathy (DR) screening in Japan. This evaluation compared the simultaneous introduction of AI in nationwide health checkups, namely "specific health check-up...

UK Biobank MRI data can power the development of generalizable brain clocks: A study of standard ML/DL methodologies and performance analysis on external databases.

NeuroImage
In this study, we present a comprehensive pipeline to train and compare a broad spectrum of machine learning and deep learning brain clocks, integrating diverse preprocessing strategies and correction terms. Our analysis also includes established met...

The use of artificial intelligence to aid the diagnosis of lung cancer - A retrospective-cohort study.

Radiography (London, England : 1995)
INTRODUCTION: AI software in the form of deep learning-based automatic detection (DLAD) algorithms for chest X-ray (CXR) interpretation have shown success in early detection of lung cancer (LC), however, there remains uncertainty related to clinical ...

High resolution multi-delay arterial spin labeling with self-supervised deep learning denoising for pediatric choroid plexus perfusion MRI.

NeuroImage
Choroid plexus (CP) is an important brain structure that produces cerebrospinal fluid (CSF). CP perfusion has been studied using multi-delay arterial spin labeling (MD-ASL) in adults but not in pediatric populations due to the challenge of small CP s...

On the relationship between music students' negative emotions, artificial intelligence readiness, and their engagement.

Acta psychologica
This study explored the relationship between negative emotions, engagement, and artificial intelligence (AI) readiness among 323 music students. The researchers employed SPSS (version 27) and AMOS (version 24) for analysis using the Emotion Beliefs Q...

Predicting conversion in cognitively normal and mild cognitive impairment individuals with machine learning: Is the CSF status still relevant?

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Machine learning (ML) helps diagnose the mild cognitive impairment-Alzheimer's disease (MCI-AD) spectrum. However, ML is fed with data unavailable in standard clinical practice. Thus, we tested a novel multi-step ML approach to predict ...