AIMC Topic:
Predictive Value of Tests

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A machine learning model for the prediction of survival and tumor subtype in pancreatic ductal adenocarcinoma from preoperative diffusion-weighted imaging.

European radiology experimental Oct 17, 2019
BACKGROUND: To develop a supervised machine learning (ML) algorithm predicting above- versus below-median overall survival (OS) from diffusion-weighted imaging-derived radiomic features in patients with pancreatic ductal adenocarcinoma (PDAC).
Predictive Value of Tests Carcinoma, Pancreatic Ductal Preoperative Period Diffusion Magnetic Resonance Imaging Machine Learning Retrospective Studies Survival Rate Models, Theoretical Pancreatic Neoplasms Humans
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Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ.

Computers in biology and medicine Oct 16, 2019
PURPOSE: To determine whether deep learning-based algorithms applied to breast MR images can aid in the prediction of occult invasive disease following the diagnosis of ductal carcinoma in situ (DCIS) by core needle biopsy.
Predictive Value of Tests Carcinoma, Ductal, Breast Biopsy, Fine-Needle Breast Neoplasms Middle Aged Deep Learning Humans Support Vector Machine Retrospective Studies Magnetic Resonance Imaging Female Aged Adult
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Extreme Gradient Boosting Model Has a Better Performance in Predicting the Risk of 90-Day Readmissions in Patients with Ischaemic Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Oct 16, 2019
OBJECT: Ischemic stroke readmission within 90 days of hospital discharge is an important quality of care metric. The readmission rates of ischemic stroke patients are usually higher than those of patients with other chronic diseases. Our aim was to i...
Stroke Humans Patient Readmission Male Machine Learning Brain Ischemia Retrospective Studies Middle Aged Decision Support Techniques Recurrence Female Risk Assessment Reproducibility of Results Time Factors Risk Factors Predictive Value of Tests Aged
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Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning.

Medical image analysis Oct 15, 2019
CT Perfusion (CTP) imaging has gained importance in the diagnosis of acute stroke. Conventional perfusion analysis performs a deconvolution of the measurements and thresholds the perfusion parameters to determine the tissue status. We pursue a data-d...
Datasets as Topic Cerebral Angiography Multicenter Studies as Topic Randomized Controlled Trials as Topic Predictive Value of Tests Radiographic Image Interpretation, Computer-Assisted Cerebral Infarction Female Humans Aged Tomography, X-Ray Computed Male Middle Aged Deep Learning
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Recurrent Neural Networks for Early Detection of Heart Failure From Longitudinal Electronic Health Record Data: Implications for Temporal Modeling With Respect to Time Before Diagnosis, Data Density, Data Quantity, and Data Type.

Circulation. Cardiovascular quality and outcomes Oct 15, 2019
BACKGROUND: We determined the impact of data volume and diversity and training conditions on recurrent neural network methods compared with traditional machine learning methods.
Electronic Health Records Vital Signs Female Reproducibility of Results Risk Factors Heart Failure Humans Male Early Diagnosis Primary Health Care Neural Networks, Computer Smoking Diagnosis, Computer-Assisted Longitudinal Studies Machine Learning Alcohol Drinking Incidence Predictive Value of Tests California Time Factors
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Atrial Fibrillation Burden Signature and Near-Term Prediction of Stroke: A Machine Learning Analysis.

Circulation. Cardiovascular quality and outcomes Oct 15, 2019
BACKGROUND: Atrial fibrillation (AF) increases the risk of stroke 5-fold and there is rising interest to determine if AF severity or burden can further risk stratify these patients, particularly for near-term events. Using continuous remote monitorin...
Stroke Atrial Fibrillation Proof of Concept Study Administrative Claims, Healthcare Telemetry Time Factors Logistic Models United States Predictive Value of Tests Signal Processing, Computer-Assisted Veterans Health Services Retrospective Studies Electronic Health Records Female Risk Factors Aged Aged, 80 and over Male Middle Aged Risk Assessment Diagnosis, Computer-Assisted Humans Neural Networks, Computer Machine Learning Prognosis
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A comparative study of machine learning classifiers for risk prediction of asthma disease.

Photodiagnosis and photodynamic therapy Oct 12, 2019
Asthma is a chronic disease characterized by wheezing, chest tightening and difficulty in breathing due to inflammation of lung airways. Early risk prediction of asthma is crucial for proper and effective management. This study presents the use of ma...
Humans Neural Networks, Computer Machine Learning Female Aged Adult Asthma Male Middle Aged Case-Control Studies Support Vector Machine Spectrum Analysis, Raman Predictive Value of Tests
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Identification and Quantification of Cardiovascular Structures From CCTA: An End-to-End, Rapid, Pixel-Wise, Deep-Learning Method.

JACC. Cardiovascular imaging Oct 11, 2019
OBJECTIVES: This study designed and evaluated an end-to-end deep learning solution for cardiac segmentation and quantification.
Aged Male Middle Aged Deep Learning Predictive Value of Tests Coronary Angiography Humans Prospective Studies Female Reproducibility of Results Radiographic Image Interpretation, Computer-Assisted Registries Heart Diseases Multidetector Computed Tomography Computed Tomography Angiography
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Deep Learning in Quantitative PET Myocardial Perfusion Imaging: A Study on Cardiovascular Event Prediction.

JACC. Cardiovascular imaging Oct 11, 2019
Coronary Artery Disease Image Interpretation, Computer-Assisted Myocardial Perfusion Imaging Models, Cardiovascular Aged Humans Male Prognosis Middle Aged Female Risk Assessment Reproducibility of Results Disease Progression Risk Factors Diagnosis, Computer-Assisted Deep Learning Time Factors Predictive Value of Tests Positron Emission Tomography Computed Tomography
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The use of a machine-learning algorithm that predicts hypotension during surgery in combination with personalized treatment guidance: study protocol for a randomized clinical trial.

Trials Oct 11, 2019
BACKGROUND: Intraoperative hypotension is associated with increased morbidity and mortality. Current treatment is mostly reactive. The Hypotension Prediction Index (HPI) algorithm is able to predict hypotension minutes before the blood pressure actua...
Machine Learning Decision Support Techniques Prospective Studies Risk Factors Risk Assessment Randomized Controlled Trials as Topic Humans Predictive Value of Tests Time Factors Hypotension Monitoring, Intraoperative Netherlands Blood Pressure Determination Surgical Procedures, Operative Treatment Outcome Arterial Pressure Intraoperative Period
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