AIMC Topic: Predictive Value of Tests

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Neural Network Vessel Lumen Regression for Automated Lumen Cross-Section Segmentation in Cardiovascular Image-Based Modeling.

Cardiovascular engineering and technology Nov 11, 2020
PURPOSE: We accelerate a pathline-based cardiovascular model building method by training machine learning models to directly predict vessel lumen surface points from computed tomography (CT) and magnetic resonance (MR) medical image data.
Models, Cardiovascular Patient-Specific Modeling Blood Vessels Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Automation Magnetic Resonance Angiography Computed Tomography Angiography Humans Neural Networks, Computer Reproducibility of Results Diagnosis, Computer-Assisted
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Machine Learned Cellular Phenotypes in Cardiomyopathy Predict Sudden Death.

Circulation research Nov 10, 2020
RATIONALE: Susceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside.
Risk Factors Aged Aged, 80 and over Male Middle Aged Risk Assessment Diagnosis, Computer-Assisted Time Factors Neural Networks, Computer Support Vector Machine Phenotype Action Potentials Predictive Value of Tests Prospective Studies Cardiomyopathies Humans Signal Processing, Computer-Assisted Prognosis Ventricular Fibrillation Myocardial Infarction Female Death, Sudden, Cardiac Tachycardia, Ventricular Electrophysiologic Techniques, Cardiac
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Deep learning-based clustering robustly identified two classes of sepsis with both prognostic and predictive values.

EBioMedicine Nov 10, 2020
BACKGROUND: Sepsis is a heterogenous syndrome and individualized management strategy is the key to successful treatment. Genome wide expression profiling has been utilized for identifying subclasses of sepsis, but the clinical utility of these subcla...
Sepsis Humans ROC Curve Disease Susceptibility Computational Biology Male Algorithms Cluster Analysis Gene Expression Profiling Biomarkers Predictive Value of Tests Transcriptome Prognosis Deep Learning Female
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Deep Learning for Osteoporosis Classification Using Hip Radiographs and Patient Clinical Covariates.

Biomolecules Nov 10, 2020
This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective labeling, we collected a dataset containing 1131 im...
Deep Learning Female Humans ROC Curve Aged Predictive Value of Tests Neural Networks, Computer Radiography Bone Density Hip Osteoporosis Aged, 80 and over Male Middle Aged
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Predicting suicide attempt or suicide death following a visit to psychiatric specialty care: A machine learning study using Swedish national registry data.

PLoS medicine Nov 6, 2020
BACKGROUND: Suicide is a major public health concern globally. Accurately predicting suicidal behavior remains challenging. This study aimed to use machine learning approaches to examine the potential of the Swedish national registry data for predict...
Depressive Disorder, Major Suicide, Attempted Suicidal Ideation Predictive Value of Tests Registries Young Adult Adult Male Risk Assessment Humans Machine Learning Female Sweden Risk Factors
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Two machine learning methods identify a metastasis-related prognostic model that predicts overall survival in medulloblastoma patients.

Aging Nov 5, 2020
Approximately 30% of medulloblastoma (MB) patients exhibit metastasis at initial diagnosis, which often leads to a poor prognosis. Here, by using univariate Cox regression analysis, two machine learning methods (Lasso-penalized Cox regression and ran...
Nomograms Databases, Genetic Predictive Value of Tests Cerebellar Neoplasms Medulloblastoma Gene Expression Profiling Transcriptome Adolescent Child, Preschool Male Child Middle Aged Risk Assessment Infant Machine Learning Reproducibility of Results Risk Factors Decision Support Techniques Humans Young Adult Adult Prognosis Biomarkers, Tumor Clinical Decision-Making Female
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Consistency of variety of machine learning and statistical models in predicting clinical risks of individual patients: longitudinal cohort study using cardiovascular disease as exemplar.

BMJ (Clinical research ed.) Nov 4, 2020
OBJECTIVE: To assess the consistency of machine learning and statistical techniques in predicting individual level and population level risks of cardiovascular disease and the effects of censoring on risk predictions.
Cardiovascular Diseases Middle Aged Risk Assessment England Longitudinal Studies Humans Machine Learning Female Adult Male Calibration Medical Record Linkage Decision Making Models, Statistical Predictive Value of Tests Survival Analysis
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Machine learning models to predict length of stay and discharge destination in complex head and neck surgery.

Head & neck Nov 3, 2020
BACKGROUND: This study develops machine learning (ML) algorithms that use preoperative-only features to predict discharge-to-nonhome-facility (DNHF) and length-of-stay (LOS) following complex head and neck surgeries.
Humans Length of Stay Machine Learning Predictive Value of Tests Algorithms Patient Discharge
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Challenges Developing Deep Learning Algorithms in Cytology.

Acta cytologica Nov 2, 2020
BACKGROUND: The incorporation of digital pathology into routine pathology practice is becoming more widespread. Definite advantages exist with respect to the implementation of artificial intelligence (AI) and deep learning in pathology, including cyt...
Humans Cytodiagnosis Automation, Laboratory Image Interpretation, Computer-Assisted Reproducibility of Results Quality Indicators, Health Care Diagnosis, Computer-Assisted Computer Security Deep Learning Pathology Predictive Value of Tests
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Prediction of amyloid β PET positivity using machine learning in patients with suspected cerebral amyloid angiopathy markers.

Scientific reports Nov 2, 2020
Amyloid-β(Aβ) PET positivity in patients with suspected cerebral amyloid angiopathy (CAA) MRI markers is predictive of a worse cognitive trajectory, and it provides insights into the underlying vascular pathology (CAA vs. hypertensive angiopathy) to ...
Magnetic Resonance Imaging Predictive Value of Tests Humans Amyloid beta-Peptides Machine Learning Cerebral Amyloid Angiopathy Aged Algorithms Aged, 80 and over Biomarkers Male Brain ROC Curve Prognosis Cognition Female
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