AIMC Topic:
Predictive Value of Tests
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Machine learning improves prediction of delayed cerebral ischemia in patients with subarachnoid hemorrhage.
Journal of neurointerventional surgery
Nov 10, 2018
BACKGROUND AND PURPOSE: Delayed cerebral ischemia (DCI) is a severe complication in patients with aneurysmal subarachnoid hemorrhage. Several associated predictors have been previously identified. However, their predictive value is generally low. We ...
Mortality prediction in patients with isolated moderate and severe traumatic brain injury using machine learning models.
PloS one
Nov 9, 2018
BACKGROUND: The purpose of this study was to build a model of machine learning (ML) for the prediction of mortality in patients with isolated moderate and severe traumatic brain injury (TBI).
Machine learning predicts individual cancer patient responses to therapeutic drugs with high accuracy.
Scientific reports
Nov 6, 2018
Precision or personalized cancer medicine is a clinical approach that strives to customize therapies based upon the genomic profiles of individual patient tumors. Machine learning (ML) is a computational method particularly suited to the establishmen...
Variable generalization performance of a deep learning model to detect pneumonia in chest radiographs: A cross-sectional study.
PLoS medicine
Nov 6, 2018
BACKGROUND: There is interest in using convolutional neural networks (CNNs) to analyze medical imaging to provide computer-aided diagnosis (CAD). Recent work has suggested that image classification CNNs may not generalize to new data as well as previ...
Retrospective Studies
Female
Reproducibility of Results
Aged
Adult
Humans
Deep Learning
United States
Pneumonia
Predictive Value of Tests
Radiographic Image Interpretation, Computer-Assisted
Cross-Sectional Studies
Male
Middle Aged
Diagnosis, Computer-Assisted
Radiology Information Systems
Radiography, Thoracic
Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study.
PLoS medicine
Nov 6, 2018
BACKGROUND: Electronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary fo...
Predicting conversion from clinically isolated syndrome to multiple sclerosis-An imaging-based machine learning approach.
NeuroImage. Clinical
Nov 5, 2018
Magnetic resonance imaging (MRI) scans play a pivotal role in the evaluation of patients presenting with a clinically isolated syndrome (CIS), as these may depict brain lesions suggestive of an inflammatory cause. We hypothesized that it is possible ...
A Predictive Model for Guillain-Barré Syndrome Based on Ensemble Methods.
Computational intelligence and neuroscience
Nov 5, 2018
Nowadays, Machine Learning methods have proven to be highly effective on the identification of various types of diseases, in the form of predictive models. Guillain-Barré syndrome (GBS) is a potentially fatal autoimmune neurological disorder that has...
Machine learning to predict lung nodule biopsy method using CT image features: A pilot study.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Nov 3, 2018
Computed tomography (CT)-based screening on lung cancer mortality is poised to make lung nodule management a growing public health problem. Biopsy and pathologic analysis of suspicious nodules is necessary to ensure accurate diagnosis and appropriate...
Using an artificial neural network to predict traumatic brain injury.
Journal of neurosurgery. Pediatrics
Nov 2, 2018
In BriefPediatric traumatic brain injury (TBI) is common, but not all injuries require hospitalization. A computational tool for ruling-in patients who will have clinically relevant TBI (CRTBI) would be valuable, providing an evidence-based mechanism...
Deep learning provides a new computed tomography-based prognostic biomarker for recurrence prediction in high-grade serous ovarian cancer.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Nov 1, 2018
BACKGROUND AND PURPOSE: Recurrence is the main risk for high-grade serous ovarian cancer (HGSOC) and few prognostic biomarkers were reported. In this study, we proposed a novel deep learning (DL) method to extract prognostic biomarkers from preoperat...
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