AI Medical Compendium Topic:
Cross-Sectional Studies

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Needs Assessment Survey Identifying Research Processes Which may be Improved by Automation or Artificial Intelligence: ICU Community Modeling and Artificial Intelligence to Improve Efficiency (ICU-Comma).

Journal of intensive care medicine
BACKGROUND: Critical care research in Canada is conducted primarily in academically-affiliated intensive care units with established research infrastructure, including research coordinators (RCs). Recently, efforts have been made to engage community ...

A Multilayer Perceptron Neural Network Model to Classify Hypertension in Adolescents Using Anthropometric Measurements: A Cross-Sectional Study in Sarawak, Malaysia.

Computational and mathematical methods in medicine
This study outlines and developed a multilayer perceptron (MLP) neural network model for adolescent hypertension classification focusing on the use of simple anthropometric and sociodemographic data collected from a cross-sectional research study in ...

Left ventricular systolic dysfunction predicted by artificial intelligence using the electrocardiogram in Chagas disease patients-The SaMi-Trop cohort.

PLoS neglected tropical diseases
BACKGROUND: Left ventricular systolic dysfunction (LVSD) in Chagas disease (ChD) is relatively common and its treatment using low-cost drugs can improve symptoms and reduce mortality. Recently, an artificial intelligence (AI)-enabled ECG algorithm sh...

The effect of a post-scan processing denoising system on image quality and morphometric analysis.

Journal of neuroradiology = Journal de neuroradiologie
PURPOSE: MR image quality and subsequent brain morphometric analysis are inevitably affected by noise. The purpose of this study was to evaluate the effectiveness of an artificial intelligence (AI)-based post-scan processing denoising system, intelli...

Application of information theoretic feature selection and machine learning methods for the development of genetic risk prediction models.

Scientific reports
In view of the growth of clinical risk prediction models using genetic data, there is an increasing need for studies that use appropriate methods to select the optimum number of features from a large number of genetic variants with a high degree of r...

Deep neural network for video colonoscopy of ulcerative colitis: a cross-sectional study.

The lancet. Gastroenterology & hepatology
BACKGROUND: A combination of endoscopic and histological evaluation is important in the management of patients with ulcerative colitis. We aimed to adapt our previous deep neural network system (deep neural ulcerative colitis [DNUC]) to full video co...

A machine learning framework for the evaluation of myocardial rotation in patients with noncompaction cardiomyopathy.

PloS one
AIMS: Noncompaction cardiomyopathy (NCC) is considered a genetic cardiomyopathy with unknown pathophysiological mechanisms. We propose to evaluate echocardiographic predictors for rigid body rotation (RBR) in NCC using a machine learning (ML) based m...

A deep learning model for identifying diabetic retinopathy using optical coherence tomography angiography.

Scientific reports
As the prevalence of diabetes increases, millions of people need to be screened for diabetic retinopathy (DR). Remarkable advances in technology have made it possible to use artificial intelligence to screen DR from retinal images with high accuracy ...

Network analysis of trauma in patients with early-stage psychosis.

Scientific reports
Childhood trauma (ChT) is a risk factor for psychosis. Negative lifestyle factors such as rumination, negative schemas, and poor diet and exercise are common in psychosis. The present study aimed to perform a network analysis of interactions between ...

Effect of data leakage in brain MRI classification using 2D convolutional neural networks.

Scientific reports
In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neurological diseases from magnetic resonance imaging (MRI) data due to their potential to discern subtle and intricate patterns. Despite the high perform...