AIMC Topic: Reproducibility of Results

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Integrating deep learning with ECG, heart rate variability and demographic data for improved detection of atrial fibrillation.

Open heart
BACKGROUND: Atrial fibrillation (AF) is a common but often undiagnosed condition, increasing the risk of stroke and heart failure. Early detection is crucial, yet traditional methods struggle with AF's transient nature. This study investigates how au...

Automated mitochondrial oxygen consumption (mitoVO) analysis via a bi-directional long short-term memory neural network.

Journal of clinical monitoring and computing
Monitoring in vivo mitochondrial oxygen tension (mitoPO) enables the measurement of mitochondrial oxygen consumption (mitoVO), providing deeper insights into the skin's mitochondrial environment. However, current mitoVO analysis often relies on manua...

Multimodal Deep Learning for Grading Carpal Tunnel Syndrome: A Multicenter Study in China.

Academic radiology
RATIONALE AND OBJECTIVES: Ultrasound (US)-based deep learning (DL) models for grading the severity of carpal tunnel syndrome (CTS) are scarce. We aimed to advance CTS grading by developing a joint-DL model integrating clinical information and multimo...

Exploring the Incremental Value of Aorta Enhancement Normalization Method in Evaluating Renal Cell Carcinoma Histological Subtypes: A Multi-center Large Cohort Study.

Academic radiology
RATIONALE AND OBJECTIVES: The classification of renal cell carcinoma (RCC) histological subtypes plays a crucial role in clinical diagnosis. However, traditional image normalization methods often struggle with discrepancies arising from differences i...

Machine Learning-Assisted Health Economics and Policy Reviews: A Comparative Assessment.

Applied health economics and health policy
INTRODUCTION: The growth of scientific literature in health economics and policy represents a challenge for researchers conducting literature reviews. This study explores the adoption of a machine learning (ML) tool to enhance title and abstract scre...

Machine learning models for predicting metabolic dysfunction-associated steatotic liver disease prevalence using basic demographic and clinical characteristics.

Journal of translational medicine
BACKGROUND: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global health concern that necessitates early screening and timely intervention to improve prognosis. The current diagnostic protocols for MASLD involve complex procedu...

Comparative Assessment of Manual Segmentation of Cerebral Infarction Lesions in Experimental Animals Based on Magnetic Resonance Imaging Using Artificial Intelligence.

Bulletin of experimental biology and medicine
The aim of this study was to evaluate the quality of manual segmentation of cerebral infarction lesions in experimental animals with modeled brain infarct based on magnetic resonance imaging compared to an automated artificial intelligence approach. ...

Spanish language version of the "Medical Quality Video Evaluation Tool" (MQ-VET): Cross-cultural AI-supported adaptation and validation study.

Science progress
BACKGROUND: The Medical Quality Video Evaluation Tool (MQ-VET) is a standardized instrument for assessing health-related video quality, yet it is only available in English. This study addresses the growing demand for a Spanish version to better suppo...

Construction and validation of a predictive model for intracardiac thrombus risk in patients with dilated cardiomyopathy: a retrospective study.

BMC cardiovascular disorders
BACKGROUND: Systemic embolic events due to exfoliation of intracardiac thrombus (ICT) are one of the catastrophic complications of dilated cardiomyopathy (DCM). This study intended to develop a prediction model to predict the risk of ICT in patients ...

The NERVE-ML (neural engineering reproducibility and validity essentials for machine learning) checklist: ensuring machine learning advances neural engineering.

Journal of neural engineering
Machine learning's (MLs) ability to capture intricate patterns makes it vital in neural engineering research. With its increasing use, ensuring the validity and reproducibility of ML methods is critical. Unfortunately, this has not always been the ca...