AIMC Topic: Case-Control Studies

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Accurately Discriminating COVID-19 from Viral and Bacterial Pneumonia According to CT Images Via Deep Learning.

Interdisciplinary sciences, computational life sciences Feb 27, 2021
Computed tomography (CT) is one of the most efficient diagnostic methods for rapid diagnosis of the widespread COVID-19. However, reading CT films brings a lot of concentration and time for doctors. Therefore, it is necessary to develop an automatic ...
Pneumonia, Viral Reproducibility of Results Lung Case-Control Studies Diagnosis, Computer-Assisted Deep Learning Diagnosis, Differential Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Multidetector Computed Tomography Pneumonia, Bacterial Humans COVID-19
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Deep learning differentiates between healthy and diabetic mouse ears from optical coherence tomography angiography images.

Annals of the New York Academy of Sciences Feb 26, 2021
We trained a deep learning algorithm to use skin optical coherence tomography (OCT) angiograms to differentiate between healthy and type 2 diabetic mice. OCT angiograms were acquired with a custom-built OCT system based on an akinetic swept laser at ...
Animals Case-Control Studies Deep Learning ROC Curve Image Processing, Computer-Assisted Machine Learning Algorithms Female Reproducibility of Results Ear Mice Diagnosis, Differential Tomography, Optical Coherence Diabetes Mellitus, Experimental Angiography
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Convolutional Neural Network-Based Deep Learning Model for Predicting Differential Suicidality in Depressive Patients Using Brain Generalized q-Sampling Imaging.

The Journal of clinical psychiatry Feb 23, 2021
OBJECTIVE: Suicide is a priority health problem. Suicide assessment depends on imperfect clinician assessment with minimal ability to predict the risk of suicide. Machine learning/deep learning provides an opportunity to detect an individual at risk ...
Humans Neural Networks, Computer Algorithms Brain Female Young Adult Adult Male Middle Aged Magnetic Resonance Imaging Neuroimaging Depressive Disorder Interview, Psychological Risk Assessment Suicide, Attempted Case-Control Studies Deep Learning Suicidal Ideation
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Efficacy of Smart Speaker-Based Metamemory Training in Older Adults: Case-Control Cohort Study.

Journal of medical Internet research Feb 16, 2021
BACKGROUND: Metamemory training (MMT) is a useful training strategy for improving cognitive functioning in the older adult population. Despite the advantages, there are limitations imposed by location and time constraints.
Humans Artificial Intelligence Female Male Middle Aged Case-Control Studies Cohort Studies Teaching Metacognition
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Plasma d-glutamate levels for detecting mild cognitive impairment and Alzheimer's disease: Machine learning approaches.

Journal of psychopharmacology (Oxford, England) Feb 15, 2021
BACKGROUND: d-glutamate, which is involved in N-methyl-d-aspartate receptor modulation, may be associated with cognitive ageing.
Algorithms Biomarkers Female Aged Aged, 80 and over Humans Machine Learning Psychiatric Status Rating Scales Cognitive Dysfunction Sensitivity and Specificity Diagnosis, Differential Male Chromatography, High Pressure Liquid Middle Aged Alzheimer Disease Severity of Illness Index Glutamic Acid Case-Control Studies
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Relation of Quantitative Histologic and Radiologic Breast Tissue Composition Metrics With Invasive Breast Cancer Risk.

JNCI cancer spectrum Feb 6, 2021
BACKGROUND: Benign breast disease (BBD) is a strong breast cancer risk factor, but identifying patients that might develop invasive breast cancer remains a challenge.
Odds Ratio Mammography Breast Density Biopsy Breast Diseases Breast Female Supervised Machine Learning Risk Factors Confidence Intervals Humans Case-Control Studies Aged Adult Diagnosis, Computer-Assisted Aged, 80 and over Breast Neoplasms Age Factors Young Adult Middle Aged
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Validation of a Machine Learning Brain Electrical Activity-Based Index to Aid in Diagnosing Concussion Among Athletes.

JAMA network open Feb 1, 2021
IMPORTANCE: An objective, reliable indicator of the presence and severity of concussive brain injury and of the readiness for the return to activity has the potential to reduce concussion-related disability.
Mental Status and Dementia Tests Glasgow Coma Scale Return to Sport Young Adult Machine Learning Male Prospective Studies Case-Control Studies Electroencephalography Brain Humans Adolescent Schools Female Universities Athletes Reproducibility of Results Brain Concussion Athletic Injuries
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Integrative transcriptomic, proteomic, and machine learning approach to identifying feature genes of atrial fibrillation using atrial samples from patients with valvular heart disease.

BMC cardiovascular disorders Jan 28, 2021
BACKGROUND: Atrial fibrillation (AF) is the most common arrhythmia with poorly understood mechanisms. We aimed to investigate the biological mechanism of AF and to discover feature genes by analyzing multi-omics data and by applying a machine learnin...
Gene Regulatory Networks Genetic Association Studies Proteomics Signal Transduction Databases, Genetic Middle Aged Gene Expression Profiling Bayes Theorem Transcriptome Humans Case-Control Studies Atrial Fibrillation Machine Learning Protein Interaction Maps Heart Atria Female Heart Valve Diseases Male Oligonucleotide Array Sequence Analysis
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Comparison of MPL-ANN and PLS-DA models for predicting the severity of patients with acute pancreatitis: An exploratory study.

The American journal of emergency medicine Jan 22, 2021
OBJECTIVE: Acute pancreatitis (AP) is a common inflammatory disorder that may develop into severe AP (SAP), resulting in life-threatening complications and even death. The purpose of this study was to explore two different machine learning models of ...
China Pancreatitis Sensitivity and Specificity Neutrophils Humans Male Predictive Value of Tests Machine Learning Middle Aged Least-Squares Analysis Biomarkers Severity of Illness Index Lymphocytes Female Case-Control Studies Reproducibility of Results
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Foveal avascular zone segmentation in optical coherence tomography angiography images using a deep learning approach.

Scientific reports Jan 13, 2021
The purpose of this study was to introduce a new deep learning (DL) model for segmentation of the fovea avascular zone (FAZ) in en face optical coherence tomography angiography (OCTA) and compare the results with those of the device's built-in softwa...
Fovea Centralis Tomography, Optical Coherence Healthy Volunteers Image Interpretation, Computer-Assisted Humans Diagnostic Techniques, Ophthalmological Diabetic Retinopathy Angiography Neural Networks, Computer Adult Male Retrospective Studies Middle Aged Case-Control Studies Female Deep Learning Aged
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