AIMC Topic: Predictive Value of Tests

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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...
Data Mining Sensitivity and Specificity Statistics, Nonparametric Male Guillain-Barre Syndrome Humans Decision Support Systems, Clinical Machine Learning Predictive Value of Tests Algorithms Female
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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...
Biopsy Radiographic Image Interpretation, Computer-Assisted Humans Machine Learning Tomography, X-Ray Computed Lung Neoplasms Pilot Projects Solitary Pulmonary Nodule Imaging, Three-Dimensional Predictive Value of Tests
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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...
Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed False Positive Reactions Child Female Brain Injuries, Traumatic Sensitivity and Specificity Male Predictive Value of Tests Adolescent Area Under Curve
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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...
Prognosis Tomography, X-Ray Computed Female Biomarkers, Tumor Humans Precision Medicine Predictive Value of Tests Neoplasm Recurrence, Local Disease-Free Survival Kaplan-Meier Estimate Cystadenocarcinoma, Serous Middle Aged Deep Learning Cohort Studies Ovarian Neoplasms
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Artificial intelligence machine learning-based coronary CT fractional flow reserve (CT-FFR): Impact of iterative and filtered back projection reconstruction techniques.

Journal of cardiovascular computed tomography Oct 26, 2018
BACKGROUND: The influence of computed tomography (CT) reconstruction algorithms on the performance of machine-learning-based CT-derived fractional flow reserve (CT-FFR) has not been investigated. CT-FFR values and processing time of two reconstructio...
Coronary Vessels Computed Tomography Angiography Coronary Stenosis Fractional Flow Reserve, Myocardial Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Workflow Male Machine Learning Middle Aged Female Retrospective Studies Severity of Illness Index Humans Reproducibility of Results Aged Predictive Value of Tests
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JOURNAL CLUB: Use of Gradient Boosting Machine Learning to Predict Patient Outcome in Acute Ischemic Stroke on the Basis of Imaging, Demographic, and Clinical Information.

AJR. American journal of roentgenology Oct 24, 2018
OBJECTIVE: When treatment decisions are being made for patients with acute ischemic stroke, timely and accurate outcome prediction plays an important role. The optimal rehabilitation strategy also relies on long-term outcome predictions. The decision...
Demography Predictive Value of Tests Stroke Brain Ischemia Computed Tomography Angiography Humans Algorithms Machine Learning Biomarkers Prognosis Male Retrospective Studies Tomography, X-Ray Computed Middle Aged Female Decision Trees
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Clinically validated machine learning algorithm for detecting residual diseases with multicolor flow cytometry analysis in acute myeloid leukemia and myelodysplastic syndrome.

EBioMedicine Oct 22, 2018
BACKGROUND: Multicolor flow cytometry (MFC) analysis is widely used to identify minimal residual disease (MRD) after treatment for acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS). However, current manual interpretation suffers from dr...
Female Survival Rate Leukemia, Myeloid, Acute Humans Machine Learning Myelodysplastic Syndromes Neoplasm, Residual Male Predictive Value of Tests Flow Cytometry Disease-Free Survival
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Machine-learning integration of CT histogram analysis to evaluate the composition of atherosclerotic plaques: Validation with IB-IVUS.

Journal of cardiovascular computed tomography Oct 21, 2018
BACKGROUND: To determine whether machine learning with histogram analysis of coronary CT angiography (CCTA) yields higher diagnostic performance for coronary plaque characterization than the conventional cut-off method using the median CT number.
Ultrasonography, Interventional Radiographic Image Interpretation, Computer-Assisted Coronary Artery Disease Coronary Vessels Aged Humans Male Multidetector Computed Tomography Predictive Value of Tests Machine Learning Coronary Angiography Retrospective Studies Plaque, Atherosclerotic Female Computed Tomography Angiography Reproducibility of Results
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A predictive model for high/low risk group according to oncotype DX recurrence score using machine learning.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Oct 16, 2018
BACKGROUND: Oncotype DX(ODX) is a 21-gene breast cancer recurrence score(RS) assay that aids in decision-making for chemotherapy in early-stage hormone receptor-positive(HR+)breast cancer. We developed a prediction tool using machine learning for hig...
Neoplasm Grading Patient Selection Neoplasm Invasiveness Decision Making Predictive Value of Tests Neoplasm Staging Republic of Korea Female Aged Adult Breast Neoplasms Biomarkers, Tumor Middle Aged Risk Assessment Humans Machine Learning Retrospective Studies
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Artificial Intelligence Using Open Source BI-RADS Data Exemplifying Potential Future Use.

Journal of the American College of Radiology : JACR Oct 15, 2018
OBJECTIVES: With much hype about artificial intelligence (AI) rendering radiologists redundant, a simple radiologist-augmented AI workflow is evaluated; the premise is that inclusion of a radiologist's opinion into an AI algorithm would make the algo...
Humans Artificial Intelligence Predictive Value of Tests Algorithms Female Breast Neoplasms Diagnosis, Computer-Assisted
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