AIMC Topic: Case-Control Studies

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Convolutional neural network models for cancer type prediction based on gene expression.

BMC medical genomics Apr 3, 2020
BACKGROUND: Precise prediction of cancer types is vital for cancer diagnosis and therapy. Through a predictive model, important cancer marker genes can be inferred. Several studies have attempted to build machine learning models for this task however...
Humans Neural Networks, Computer Prognosis Biomarkers, Tumor Neoplasms Gene Expression Profiling Case-Control Studies Gene Regulatory Networks Computational Biology Gene Expression Regulation, Neoplastic
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Dynamic ElecTronic hEalth reCord deTection (DETECT) of individuals at risk of a first episode of psychosis: a case-control development and validation study.

The Lancet. Digital health Mar 26, 2020
BACKGROUND: Many individuals who will experience a first episode of psychosis (FEP) are not detected before occurrence, limiting the effect of preventive interventions. The combination of machine-learning methods and electronic health records (EHRs) ...
Humans Prognosis Neural Networks, Computer Retrospective Studies Machine Learning Data Management Middle Aged Electronic Health Records Data Analysis Area Under Curve Female Risk Assessment Delivery of Health Care Models, Biological Adult Case-Control Studies Databases, Factual Schizophrenia Male Cohort Studies ROC Curve Psychotic Disorders Datasets as Topic
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Exploring the effect of hypertension on retinal microvasculature using deep learning on East Asian population.

PloS one Mar 5, 2020
Hypertension is the leading risk factor of cardiovascular disease and has profound effects on both the structure and function of the microvasculature. Abnormalities of the retinal vasculature may reflect the degree of microvascular damage due to hype...
Image Processing, Computer-Assisted Hypertension Adult Retinal Diseases Microvessels Male Humans Fluorescein Angiography Middle Aged Asia, Eastern Algorithms Retinal Vessels Case-Control Studies Female Deep Learning Aged Aged, 80 and over
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A machine learning-based linguistic battery for diagnosing mild cognitive impairment due to Alzheimer's disease.

PloS one Mar 5, 2020
There is a limited evaluation of an independent linguistic battery for early diagnosis of Mild Cognitive Impairment due to Alzheimer's disease (MCI-AD). We hypothesized that an independent linguistic battery comprising of only the language components...
Neuropsychological Tests Linguistics Male Case-Control Studies Humans Cognitive Dysfunction Machine Learning Alzheimer Disease Female Cognition Disorders Aged, 80 and over
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Pragmatics, Theory of Mind and executive functions in schizophrenia: Disentangling the puzzle using machine learning.

PloS one Mar 3, 2020
OBJECTIVE: Schizophrenia is associated with a severe impairment in the communicative-pragmatic domain. Recent research has tried to disentangle the relationship between communicative impairment and other domains usually impaired in schizophrenia, i.e...
Social Communication Disorder Humans Case-Control Studies Cognition Young Adult Machine Learning Models, Psychological Bayes Theorem Female Adult Linguistics Memory, Short-Term Communication Schizophrenic Psychology Schizophrenia Male Theory of Mind Neuropsychological Tests Middle Aged Executive Function
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Machine learning on genome-wide association studies to predict the risk of radiation-associated contralateral breast cancer in the WECARE Study.

PloS one Feb 27, 2020
The purpose of this study was to identify germline single nucleotide polymorphisms (SNPs) that optimally predict radiation-associated contralateral breast cancer (RCBC) and to provide new biological insights into the carcinogenic process. Fifty-two w...
Young Adult Adult Breast Neoplasms Case-Control Studies Genome-Wide Association Study Cohort Studies Polymorphism, Single Nucleotide Genotype Cancer Survivors Germ Cells Neoplasms, Radiation-Induced Humans Machine Learning Female Risk Factors
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Macular Ganglion Cell-Inner Plexiform Layer Thickness Prediction from Red-free Fundus Photography using Hybrid Deep Learning Model.

Scientific reports Feb 24, 2020
We developed a hybrid deep learning model (HDLM) algorithm that quantitatively predicts macular ganglion cell-inner plexiform layer (mGCIPL) thickness from red-free retinal nerve fiber layer photographs (RNFLPs). A total of 789 pairs of RNFLPs and sp...
ROC Curve Support Vector Machine Regression Analysis Optic Nerve Tomography, Optical Coherence Male Middle Aged Case-Control Studies Diagnosis, Computer-Assisted Deep Learning Fundus Oculi Translational Research, Biomedical Retinal Ganglion Cells Diagnostic Techniques, Ophthalmological Refractometry Humans Glaucoma Algorithms Retrospective Studies Female Aged Aged, 80 and over Young Adult Adult Sensitivity and Specificity Intraocular Pressure
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Assessment of liver fibrosis severity using computed tomography-based liver and spleen volumetric indices in patients with chronic liver disease.

European radiology Feb 13, 2020
OBJECTIVES: To evaluate whether the liver and spleen volumetric indices, measured on portal venous phase CT images, could be used to assess liver fibrosis severity in chronic liver disease.
ROC Curve Liver Cirrhosis Male Liver Humans Middle Aged Chronic Disease Liver Diseases Retrospective Studies Severity of Illness Index Organ Size Spleen Tomography, X-Ray Computed Case-Control Studies Deep Learning Female Adult
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Diagnosis of ventilator-associated pneumonia using electronic nose sensor array signals: solutions to improve the application of machine learning in respiratory research.

Respiratory research Feb 7, 2020
BACKGROUND: Ventilator-associated pneumonia (VAP) is a significant cause of mortality in the intensive care unit. Early diagnosis of VAP is important to provide appropriate treatment and reduce mortality. Developing a noninvasive and highly accurate ...
Case-Control Studies Decision Trees Respiratory Mechanics Pneumonia, Ventilator-Associated Electronic Nose Aged Humans Aged, 80 and over Machine Learning Biomedical Research Intensive Care Units Male Female Middle Aged
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Novel biomarker genes which distinguish between smokers and chronic obstructive pulmonary disease patients with machine learning approach.

BMC pulmonary medicine Feb 3, 2020
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is combination of progressive lung diseases. The diagnosis of COPD is generally based on the pulmonary function testing, however, difficulties underlie in prognosis of smokers or early stage of...
Humans Machine Learning Biomarkers Female Adult Pulmonary Disease, Chronic Obstructive Logistic Models Epithelial Cells Cigarette Smoking Gene Expression Regulation Smokers Male Middle Aged Lung Gene Expression Profiling Case-Control Studies
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