AIMC Topic: Predictive Value of Tests

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Machine learning analysis of MRI-derived texture features to predict placenta accreta spectrum in patients with placenta previa.

Magnetic resonance imaging May 15, 2019
PURPOSE: To evaluate whether a machine learning (ML) analysis employing MRI-derived texture analysis (TA) features could be useful in assessing the presence of placenta accreta spectrum (PAS) in patients with placenta previa (PP). The hypothesis is t...
Bayes Theorem Placenta Image Interpretation, Computer-Assisted Prenatal Diagnosis Placenta Accreta Reproducibility of Results Adult Sensitivity and Specificity Magnetic Resonance Imaging Predictive Value of Tests Placenta Previa Humans Machine Learning Algorithms Retrospective Studies Pregnancy Female
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Deep learning for liver tumor diagnosis part II: convolutional neural network interpretation using radiologic imaging features.

European radiology May 15, 2019
OBJECTIVES: To develop a proof-of-concept "interpretable" deep learning prototype that justifies aspects of its predictions from a pre-trained hepatic lesion classifier.
Retrospective Studies Female Aged Adult Male Humans Neural Networks, Computer Machine Learning Algorithms Bile Ducts, Intrahepatic Middle Aged Predictive Value of Tests Deep Learning Image Interpretation, Computer-Assisted Liver Neoplasms Bile Duct Neoplasms Carcinoma, Hepatocellular Proof of Concept Study Magnetic Resonance Imaging Cholangiocarcinoma
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A machine-learning-based prediction model of fistula formation after interstitial brachytherapy for locally advanced gynecological malignancies.

Brachytherapy May 15, 2019
PURPOSE: External beam radiotherapy combined with interstitial brachytherapy is commonly used to treat patients with bulky, advanced gynecologic cancer. However, the high radiation dose needed to control the tumor may result in fistula development. T...
Genital Neoplasms, Female Brachytherapy Vesicovaginal Fistula Rectovaginal Fistula Middle Aged Models, Theoretical Support Vector Machine Predictive Value of Tests Area Under Curve Risk Factors Aged Humans Aged, 80 and over Adult Retrospective Studies Female
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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...
Humans Neural Networks, Computer Machine Learning Female Reproducibility of Results Risk Factors Coronary Artery Disease Fibrosis Image Interpretation, Computer-Assisted Coronary Vessels Rupture, Spontaneous Plaque, Atherosclerotic Aged Diagnosis, Computer-Assisted Coronary Stenosis Male Predictive Value of Tests Middle Aged Tomography, Optical Coherence Risk Assessment Bayes Theorem Disease Progression Ultrasonography, Interventional
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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 ...
Machine Learning Female Reproducibility of Results Male Middle Aged Humans Tumor Burden Image Enhancement Chemoradiotherapy Diffusion Magnetic Resonance Imaging Multiparametric Magnetic Resonance Imaging Treatment Outcome Contrast Media Predictive Value of Tests Rectum Rectal Neoplasms
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Development and Validation of Machine Learning Models in Prediction of Remission in Patients With Moderate to Severe Crohn Disease.

JAMA network open May 3, 2019
IMPORTANCE: Biological therapies have revolutionized inflammatory bowel disease management, but many patients do not respond to biological monotherapy. Identification of likely responders could reduce costs and delays in remission.
Crohn Disease Remission Induction Biological Therapy Ustekinumab Humans Machine Learning Female Adult Male Middle Aged Severity of Illness Index Predictive Value of Tests C-Reactive Protein
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Effect of Tube Voltage on Diagnostic Performance of Fractional Flow Reserve Derived From Coronary CT Angiography With Machine Learning: Results From the MACHINE Registry.

AJR. American journal of roentgenology Apr 30, 2019
Coronary CT angiography (CCTA)-based methods allow noninvasive estimation of fractional flow reserve (cFFR), recently through use of a machine learning (ML) algorithm (cFFR). However, attenuation values vary according to the tube voltage used, and i...
Retrospective Studies Female Aged Sensitivity and Specificity Male Humans Machine Learning Computed Tomography Angiography Fractional Flow Reserve, Myocardial Middle Aged Predictive Value of Tests Coronary Angiography Registries Coronary Disease
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Efficient learning from big data for cancer risk modeling: A case study with melanoma.

Computers in biology and medicine Apr 30, 2019
BACKGROUND: Building cancer risk models from real-world data requires overcoming challenges in data preprocessing, efficient representation, and computational performance. We present a case study of a cloud-based approach to learning from de-identifi...
Big Data Predictive Value of Tests Models, Biological Humans Machine Learning Electronic Health Records Melanoma Risk Factors Risk Assessment
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Prediction of Alzheimer's disease dementia with MRI beyond the short-term: Implications for the design of predictive models.

NeuroImage. Clinical Apr 30, 2019
Magnetic resonance imaging (MRI) volumetric measures have become a standard tool for the detection of incipient Alzheimer's Disease (AD) dementia in mild cognitive impairment (MCI). Focused on providing an earlier and more accurate diagnosis, sophist...
Follow-Up Studies Magnetic Resonance Imaging Predictive Value of Tests Aged, 80 and over Humans Alzheimer Disease Male Machine Learning Middle Aged Female Dementia Aged Cohort Studies
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Predicting coronary artery disease: a comparison between two data mining algorithms.

BMC public health Apr 29, 2019
BACKGROUND: Cardiovascular diseases (CADs) are the first leading cause of death across the world. World Health Organization has estimated that morality rate caused by heart diseases will mount to 23 million cases by 2030. Hence, the use of data minin...
Predictive Value of Tests Coronary Artery Disease Data Mining Sex Factors Middle Aged ROC Curve Socioeconomic Factors Support Vector Machine Age Factors Electronic Health Records Female Risk Factors Male Humans Neural Networks, Computer Algorithms
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