AIMC Topic: Reproducibility of Results

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New Deep Learning Genomic-Based Prediction Model for Multiple Traits with Binary, Ordinal, and Continuous Phenotypes.

G3 (Bethesda, Md.) May 7, 2019
Multiple-trait experiments with mixed phenotypes (binary, ordinal and continuous) are not rare in animal and plant breeding programs. However, there is a lack of statistical models that can exploit the correlation between traits with mixed phenotypes...
Algorithms Phenotype Reproducibility of Results Selection, Genetic Genome Genome, Plant Quantitative Trait, Heritable Plant Breeding Deep Learning Genomics Genotype Genetic Association Studies Models, Genetic
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Physician Review of a Celiac Disease Risk Estimation and Decision-Making Expert System.

Journal of the American College of Nutrition May 7, 2019
Celiac disease is a genetic disease affecting people of all ages, resulting in small intestine enteropathy. It is considered to be a clinical chameleon. Average prevalence of celiac disease is 1 out of 100 people with data indicating the risk may be...
Celiac Disease Humans Physicians Reproducibility of Results Risk Factors Decision Making Autoantibodies Biopsy Expert Systems
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Prediction of coronary thin-cap fibroatheroma by intravascular ultrasound-based machine learning.

Atherosclerosis May 4, 2019
BACKGROUND AND AIMS: Although grayscale intravascular ultrasound (IVUS) is commonly used for assessing coronary lesion morphology and optimizing stent implantation, detection of vulnerable plaques by IVUS remains challenging. We aimed to develop mach...
Bayes Theorem Ultrasonography, Interventional Coronary Artery Disease Fibrosis Image Interpretation, Computer-Assisted Coronary Vessels Rupture, Spontaneous Plaque, Atherosclerotic Coronary Stenosis Risk Assessment Risk Factors Disease Progression Diagnosis, Computer-Assisted Aged Predictive Value of Tests Humans Male Tomography, Optical Coherence Neural Networks, Computer Middle Aged Machine Learning Female Reproducibility of Results
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Machine learning for prediction of chemoradiation therapy response in rectal cancer using pre-treatment and mid-radiation multi-parametric MRI.

Magnetic resonance imaging May 3, 2019
PURPOSE: To predict the neoadjuvant chemoradiation therapy (CRT) response in patients with locally advanced rectal cancer (LARC) using radiomics and deep learning based on pre-treatment MRI and a mid-radiation follow-up MRI taken 3-4 weeks after the ...
Male Middle Aged Treatment Outcome Contrast Media Predictive Value of Tests Humans Machine Learning Female Reproducibility of Results Diffusion Magnetic Resonance Imaging Multiparametric Magnetic Resonance Imaging Rectum Rectal Neoplasms Tumor Burden Image Enhancement Chemoradiotherapy
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Dynamic contrast-enhanced computed tomography diagnosis of primary liver cancers using transfer learning of pretrained convolutional neural networks: Is registration of multiphasic images necessary?

International journal of computer assisted radiology and surgery May 3, 2019
PURPOSE: To evaluate the effect of image registration on the diagnostic performance of transfer learning (TL) using pretrained convolutional neural networks (CNNs) and three-phasic dynamic contrast-enhanced computed tomography (DCE-CT) for primary li...
Contrast Media Tomography, Spiral Computed Male Middle Aged Liver Neoplasms Carcinoma, Hepatocellular Image Processing, Computer-Assisted Humans Neural Networks, Computer Algorithms Retrospective Studies Female Reproducibility of Results Aged
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Performance of a Deep Learning Model vs Human Reviewers in Grading Endoscopic Disease Severity of Patients With Ulcerative Colitis.

JAMA network open May 3, 2019
IMPORTANCE: Assessing endoscopic disease severity in ulcerative colitis (UC) is a key element in determining therapeutic response, but its use in clinical practice is limited by the requirement for experienced human reviewers.
Colitis, Ulcerative Video Recording Humans Male Retrospective Studies Middle Aged Female Colonoscopy Reproducibility of Results Severity of Illness Index Adult Deep Learning
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Deep learning to automate Brasfield chest radiographic scoring for cystic fibrosis.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society May 2, 2019
BACKGROUND: The aim of this study was to evaluate the hypothesis that a deep convolutional neural network (DCNN) model could facilitate automated Brasfield scoring of chest radiographs (CXRs) for patients with cystic fibrosis (CF), performing similar...
Humans Neural Networks, Computer Research Design Cystic Fibrosis Male Pediatrics Lung Radiography, Thoracic Severity of Illness Index Prognosis Deep Learning Tomography, X-Ray Computed Child Female Reproducibility of Results
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Preoperative Prediction of Value Metrics and a Patient-Specific Payment Model for Primary Total Hip Arthroplasty: Development and Validation of a Deep Learning Model.

The Journal of arthroplasty May 2, 2019
BACKGROUND: The primary objective was to develop and test an artificial neural network (ANN) that learns and predicts length of stay (LOS), inpatient charges, and discharge disposition for total hip arthroplasty. The secondary objective was to create...
Humans ROC Curve United States Inpatients Arthroplasty, Replacement, Hip Preoperative Period Social Class Male Health Care Costs Comorbidity Osteoarthritis, Hip Deep Learning Databases, Factual Fees and Charges Length of Stay Female Cohort Studies Reproducibility of Results Aged Aged, 80 and over
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A deep learning radiomics model for preoperative grading in meningioma.

European journal of radiology May 1, 2019
OBJECTIVES: To noninvasively differentiate meningioma grades by deep learning radiomics (DLR) model based on routine post-contrast MRI.
Deep Learning Adolescent Cohort Studies Magnetic Resonance Imaging Area Under Curve Young Adult Adult Sensitivity and Specificity Male Middle Aged Humans Neoplasm Grading Prognosis Algorithms Preoperative Care Retrospective Studies Meningioma Female Meningeal Neoplasms Reproducibility of Results Meninges Aged
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Computer-assisted prediction of atherosclerotic intimal thickness based on weight of adrenal gland, interleukin-6 concentration, and neural networks.

The Journal of international medical research Apr 30, 2019
OBJECTIVE: Atherosclerosis (AS) is the main pathological basis of ischemic cardio-cerebrovascular diseases, and the intimal thickness (IT) of large arteries is regarded as a powerful evaluation indicator for AS. We established an effective neural net...
Reproducibility of Results Humans Rabbits Risk Factors Neural Networks, Computer Carotid Intima-Media Thickness Animals Algorithms Adrenal Glands Organ Size Interleukin-6 Atherosclerosis
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