AIMC Topic: Retrospective Studies

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Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study.

PLoS medicine Nov 27, 2018
BACKGROUND: Pythia is an automated, clinically curated surgical data pipeline and repository housing all surgical patient electronic health record (EHR) data from a large, quaternary, multisite health institute for data science initiatives. In an eff...
Postoperative Complications Comorbidity Adolescent Health Status Data Mining Surgical Procedures, Operative Automation Young Adult Adult Male Middle Aged Humans Risk Assessment Machine Learning Female Retrospective Studies Reproducibility of Results Electronic Health Records Risk Factors Aged
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Refining Convolutional Neural Network Detection of Small-Bowel Obstruction in Conventional Radiography.

AJR. American journal of roentgenology Nov 26, 2018
OBJECTIVE: The purpose of this study was to evaluate improvement of convolutional neural network detection of high-grade small-bowel obstruction on conventional radiographs with increased training set size.
Young Adult Adult Male Middle Aged Adolescent Radiography Intestinal Obstruction Intestine, Small Neural Networks, Computer Retrospective Studies Female Aged Aged, 80 and over Humans
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Laparoscopic single-anastomosis duodenal-jejunal bypass with sleeve gastrectomy (SADJB-SG): Surgical risk and long-term results.

Surgery for obesity and related diseases : official journal of the American Society for Bariatric Surgery Nov 24, 2018
BACKGROUND: Single-anastomosis duodeno-jejunal bypass with sleeve gastrectomy (SADJB-SG) was developed as a simplified technique of DJB-SG, but long-term data are lacking.
Jejunum Time Factors Duodenum Male Treatment Outcome Laparoscopy Humans Operative Time Middle Aged Gastrectomy Retrospective Studies Postoperative Complications Gastric Bypass Female Weight Loss Obesity, Morbid Adult Anastomosis, Surgical
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Machine Learning Algorithms Utilizing Functional Respiratory Imaging May Predict COPD Exacerbations.

Academic radiology Nov 23, 2018
RATIONALE AND OBJECTIVES: Acute chronic obstructive pulmonary disease exacerbations (AECOPD) have a significant negative impact on the quality of life and accelerate progression of the disease. Functional respiratory imaging (FRI) has the potential t...
Humans Retrospective Studies Tidal Volume Airway Resistance Functional Residual Capacity Male Middle Aged Disease Progression Support Vector Machine Predictive Value of Tests Female Aged Aged, 80 and over Pulmonary Disease, Chronic Obstructive
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The Sydney Triage to Admission Risk Tool (START2) using machine learning techniques to support disposition decision-making.

Emergency medicine Australasia : EMA Nov 23, 2018
OBJECTIVE: To further develop and refine an Emergency Department (ED) in-patient admission prediction model using machine learning techniques.
Aged Aged, 80 and over Adult Male Middle Aged Machine Learning Forecasting Retrospective Studies Female Area Under Curve Emergency Service, Hospital Bayes Theorem Patient Admission New South Wales Adolescent ROC Curve Logistic Models Triage Humans
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Development and testing of a deep learning-based strategy for scar segmentation on CMR-LGE images.

Magma (New York, N.Y.) Nov 20, 2018
OBJECTIVE: The aim of this paper is to investigate the use of fully convolutional neural networks (FCNNs) to segment scar tissue in the left ventricle from cardiac magnetic resonance with late gadolinium enhancement (CMR-LGE) images.
Male Humans Heart Ventricles Deep Learning Neural Networks, Computer Gadolinium Contrast Media Retrospective Studies Image Enhancement Magnetic Resonance Imaging Female Myocardial Ischemia Cicatrix
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Automated detection of moderate and large pneumothorax on frontal chest X-rays using deep convolutional neural networks: A retrospective study.

PLoS medicine Nov 20, 2018
BACKGROUND: Pneumothorax can precipitate a life-threatening emergency due to lung collapse and respiratory or circulatory distress. Pneumothorax is typically detected on chest X-ray; however, treatment is reliant on timely review of radiographs. Sinc...
Automation Radiography, Thoracic Pneumothorax Diagnosis, Computer-Assisted Deep Learning Humans Predictive Value of Tests Databases, Factual Radiographic Image Interpretation, Computer-Assisted Prognosis Retrospective Studies Reproducibility of Results
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Deep learning for chest radiograph diagnosis: A retrospective comparison of the CheXNeXt algorithm to practicing radiologists.

PLoS medicine Nov 20, 2018
BACKGROUND: Chest radiograph interpretation is critical for the detection of thoracic diseases, including tuberculosis and lung cancer, which affect millions of people worldwide each year. This time-consuming task typically requires expert radiologis...
Humans Retrospective Studies Pneumonia Predictive Value of Tests Radiologists Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Reproducibility of Results Diagnosis, Computer-Assisted Deep Learning Clinical Competence
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Detecting abnormal electroencephalograms using deep convolutional networks.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology Nov 17, 2018
OBJECTIVES: Electroencephalography (EEG) is a central part of the medical evaluation for patients with neurological disorders. Training an algorithm to label the EEG normal vs abnormal seems challenging, because of EEG heterogeneity and dependence of...
Databases, Factual Retrospective Studies Female Young Adult Sleep Stages Adult Humans Neural Networks, Computer Male Machine Learning Middle Aged Adolescent Electroencephalography
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A deep neural network learning algorithm outperforms a conventional algorithm for emergency department electrocardiogram interpretation.

Journal of electrocardiology Nov 16, 2018
BACKGROUND: Cardiologs® has developed the first electrocardiogram (ECG) algorithm that uses a deep neural network (DNN) for full 12‑lead ECG analysis, including rhythm, QRS and ST-T-U waves. We compared the accuracy of the first version of Cardiologs...
Predictive Value of Tests Emergency Service, Hospital Arrhythmias, Cardiac Humans Neural Networks, Computer Algorithms Retrospective Studies Sensitivity and Specificity Electrocardiography
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