AIMC Topic: Case-Control Studies

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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.
Aged, 80 and over Young Adult Adult Male Machine Learning Retrospective Studies Female Aged Feasibility Studies Image Interpretation, Computer-Assisted Ear, Inner Meniere Disease Middle Aged Case-Control Studies Adolescent Magnetic Resonance Imaging Humans
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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 Middle Aged Case-Control Studies Deep Learning Aged Magnetic Resonance Imaging Aged, 80 and over Alzheimer Disease Cross-Sectional Studies Image Interpretation, Computer-Assisted Male Neuroimaging Neural Networks, Computer Parkinson Disease Brain Predictive Value of Tests Female Reproducibility of Results
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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.
Follow-Up Studies Female Magnetic Resonance Imaging Adult Brain Concussion Humans Male Case-Control Studies Machine Learning Brain Prognosis
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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...
Middle Aged Neoplasms Case-Control Studies Pilot Projects Neoplasm Staging Humans Machine Learning Female Male Heart Rate
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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 ...
Acne Vulgaris Metagenome Canonical Correlation Analysis Skin Microbiota Metagenomics Face Humans Computational Biology Lipids Principal Component Analysis Machine Learning Case-Control Studies
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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...
Computational Biology Magnetic Resonance Imaging Schizophrenia Diagnosis, Computer-Assisted Deep Learning Functional Neuroimaging ROC Curve Humans Female Adult Male Middle Aged Neural Networks, Computer Case-Control Studies Algorithms Databases, Factual Brain
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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...
Adult Asthma Male Case-Control Studies Interleukin-18 Humans Machine Learning Female
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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 ...
Machine Learning Mental Disorders Female Aged Male Middle Aged Case-Control Studies Young Adult Adult Humans Placebo Effect Adolescent Child Clinical Trials as Topic Psychotropic Drugs
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Deep learning can predict lymph node status directly from histology in colorectal cancer.

European journal of cancer (Oxford, England : 1990) Oct 11, 2021
BACKGROUND: Lymph node status is a prognostic marker and strongly influences therapeutic decisions in colorectal cancer (CRC).
Neoplasm Staging Rectum Aged ROC Curve Aged, 80 and over Image Processing, Computer-Assisted Humans Colorectal Neoplasms Lymph Nodes Prognosis Case-Control Studies Male Lymphatic Metastasis Female Deep Learning Middle Aged Cohort Studies Colon
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Global processing provides malignancy evidence complementary to the information captured by humans or machines following detailed mammogram inspection.

Scientific reports Oct 11, 2021
The information captured by the gist signal, which refers to radiologists' first impression arising from an initial global image processing, is poorly understood. We examined whether the gist signal can provide complementary information to data captu...
Female Breast Neoplasms Case-Control Studies Deep Learning Radiologists Breast Image Processing, Computer-Assisted Mammography Humans Algorithms
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