AIMC Topic: Case-Control Studies
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Machine Learning and Bioinformatics Framework Integration to Potential Familial DCM-Related Markers Discovery.
Genes
Dec 2, 2021
OBJECTIVES: Dilated cardiomyopathy (DCM) is characterized by a specific transcriptome. Since the DCM molecular network is largely unknown, the aim was to identify specific disease-related molecular targets combining an original machine learning (ML) ...
Machine Learning-based Voice Assessment for the Detection of Positive and Recovered COVID-19 Patients.
Journal of voice : official journal of the Voice Foundation
Nov 26, 2021
Many virological tests have been implemented during the Coronavirus Disease 2019 (COVID-19) pandemic for diagnostic purposes, but they appear unsuitable for screening purposes. Furthermore, current screening strategies are not accurate enough to effe...
A non-invasive, automated diagnosis of Menière's disease using radiomics and machine learning on conventional magnetic resonance imaging: A multicentric, case-controlled feasibility study.
La Radiologia medica
Nov 25, 2021
PURPOSE: This study investigated the feasibility of a new image analysis technique (radiomics) on conventional MRI for the computer-aided diagnosis of Menière's disease.
Effect of data leakage in brain MRI classification using 2D convolutional neural networks.
Scientific reports
Nov 19, 2021
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...
Humans
Neural Networks, Computer
Brain
Female
Reproducibility of Results
Middle Aged
Case-Control Studies
Deep Learning
Magnetic Resonance Imaging
Parkinson Disease
Aged
Aged, 80 and over
Cross-Sectional Studies
Male
Predictive Value of Tests
Alzheimer Disease
Image Interpretation, Computer-Assisted
Neuroimaging
Machine Learning Classification of Mild Traumatic Brain Injury Using Whole-Brain Functional Activity: A Radiomics Analysis.
Disease markers
Nov 18, 2021
OBJECTIVES: To investigate the classification performance of support vector machine in mild traumatic brain injury (mTBI) from normal controls.
Cancer classification using machine learning and HRV analysis: preliminary evidence from a pilot study.
Scientific reports
Nov 16, 2021
Most cancer patients exhibit autonomic dysfunction with attenuated heart rate variability (HRV) levels compared to healthy controls. This research aimed to create and evaluate a machine learning (ML) model enabling discrimination between cancer patie...
Metagenomic Sequencing Analysis for Acne Using Machine Learning Methods Adapted to Single or Multiple Data.
Computational and mathematical methods in medicine
Nov 13, 2021
The human health status can be assessed by the means of research and analysis of the human microbiome. Acne is a common skin disease whose morbidity increases year by year. The lipids which influence acne to a large extent are studied by metagenomic ...
Diagnosis of Schizophrenia Based on Deep Learning Using fMRI.
Computational and mathematical methods in medicine
Nov 9, 2021
Schizophrenia is a brain disease that frequently occurs in young people. Early diagnosis and treatment can reduce family burdens and reduce social costs. There is no objective evaluation index for schizophrenia. In order to improve the classification...
Machine learning implicates the IL-18 signaling axis in severe asthma.
JCI insight
Nov 8, 2021
Asthma is a common disease with profoundly variable natural history and patient morbidity. Heterogeneity has long been appreciated, and much work has focused on identifying subgroups of patients with similar pathobiological underpinnings. Previous st...
Differential power of placebo across major psychiatric disorders: a preliminary meta-analysis and machine learning study.
Scientific reports
Oct 29, 2021
The placebo effect across psychiatric disorders is still not well understood. In the present study, we conducted meta-analyses including meta-regression, and machine learning analyses to investigate whether the power of placebo effect depends on the ...
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