AIMC Topic: Retrospective Studies

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An Intelligent Clinical Decision Support System for Preoperative Prediction of Lymph Node Metastasis in Gastric Cancer.

Journal of the American College of Radiology : JACR Feb 4, 2019
PURPOSE: The aim of this study was to develop and validate a computational clinical decision support system (DSS) on the basis of CT radiomics features for the prediction of lymph node (LN) metastasis in gastric cancer (GC) using machine learning-bas...
Humans ROC Curve Decision Support Systems, Clinical Lymph Nodes Lymphatic Metastasis Female Neoplasm Invasiveness Aged Multidetector Computed Tomography Stomach Neoplasms Preoperative Care Male Middle Aged Predictive Value of Tests Neoplasm Staging Machine Learning Gastrectomy Databases, Factual Prognosis Retrospective Studies Clinical Decision-Making
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Deep convolutional neural network for the diagnosis of thyroid nodules on ultrasound.

Head & neck Feb 4, 2019
BACKGROUND: We designed a deep convolutional neural network (CNN) to diagnose thyroid malignancy on ultrasound (US) and compared the diagnostic performance of CNN with that of experienced radiologists.
ROC Curve Image Processing, Computer-Assisted Neoplasm Invasiveness Area Under Curve Neoplasm Staging Male Middle Aged Cohort Studies Thyroid Neoplasms Thyroid Nodule Observer Variation Ultrasonography, Doppler Humans Neural Networks, Computer Databases, Factual Retrospective Studies Female Adult Sensitivity and Specificity
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Automated selection of myocardial inversion time with a convolutional neural network: Spatial temporal ensemble myocardium inversion network (STEMI-NET).

Magnetic resonance in medicine Feb 3, 2019
PURPOSE: Delayed enhancement imaging is an essential component of cardiac MRI, which is used widely for the evaluation of myocardial scar and viability. The selection of an optimal inversion time (TI) or null point (TI ) to suppress the background my...
Retrospective Studies Female Aged Aged, 80 and over Young Adult Adult Humans Neural Networks, Computer Algorithms Gadolinium Contrast Media Magnetic Resonance Imaging Myocardium Heart Pattern Recognition, Automated Male Middle Aged Adolescent Child Image Processing, Computer-Assisted
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Using machine learning to optimize selection of elderly patients for endovascular thrombectomy.

Journal of neurointerventional surgery Feb 2, 2019
BACKGROUND: Endovascular thrombectomy (ET) is the standard of care for treatment of acute ischemic stroke (AIS) secondary to large vessel occlusion. The elderly population has been under-represented in clinical trials on ET, and recent studies have r...
Stroke Patient Selection Endovascular Procedures Thrombectomy Humans Machine Learning Prospective Studies Retrospective Studies Female Aged, 80 and over Male Cohort Studies Treatment Outcome
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Dose evaluation of MRI-based synthetic CT generated using a machine learning method for prostate cancer radiotherapy.

Medical dosimetry : official journal of the American Association of Medical Dosimetrists Feb 1, 2019
Magnetic resonance imaging (MRI)-only radiotherapy treatment planning is attractive since MRI provides superior soft tissue contrast over computed tomographies (CTs), without the ionizing radiation exposure. However, it requires the generation of a s...
Magnetic Resonance Imaging Prostatic Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Humans Machine Learning Retrospective Studies Tomography, X-Ray Computed Male Radiotherapy, Intensity-Modulated
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Intracranial Vessel Wall Segmentation Using Convolutional Neural Networks.

IEEE transactions on bio-medical engineering Feb 1, 2019
OBJECTIVE: To develop an automated vessel wall segmentation method using convolutional neural networks to facilitate the quantification on magnetic resonance (MR) vessel wall images of patients with intracranial atherosclerotic disease (ICAD).
Magnetic Resonance Angiography Middle Cerebral Artery Intracranial Arteriosclerosis Middle Aged Imaging, Three-Dimensional Contrast Media Image Interpretation, Computer-Assisted Automation Neural Networks, Computer Retrospective Studies Female Risk Factors Male Humans
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A Comparative Texture Analysis Based on NECT and CECT Images to Differentiate Lung Adenocarcinoma from Squamous Cell Carcinoma.

Journal of medical systems Feb 1, 2019
The purpose of the study was to compare the texture based discriminative performances between non-contrast enhanced computed tomography (NECT) and contrast-enhanced computed tomography (CECT) images in differentiating lung adenocarcinoma (ADC) from s...
Retrospective Studies Tomography, X-Ray Computed Female Carcinoma, Squamous Cell Aged Humans Aged, 80 and over Lung Neoplasms Adult Socioeconomic Factors Male Support Vector Machine Middle Aged Contrast Media Image Processing, Computer-Assisted Diagnosis, Differential Adenocarcinoma of Lung
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Natural Language Processing-Identified Problem Opioid Use and Its Associated Health Care Costs.

Journal of pain & palliative care pharmacotherapy Jan 31, 2019
Use of prescription opioids and problems of abuse and addiction have increased over the past decade. Claims-based studies have documented substantial economic burden of opioid abuse. This study utilized electronic health record (EHR) data to identify...
Adolescent United States Young Adult Longitudinal Studies Humans Adult Follow-Up Studies Retrospective Studies Analgesics, Opioid Male Natural Language Processing Electronic Health Records Medicare Middle Aged Female Opioid-Related Disorders Case-Control Studies Aged Health Care Costs Cost of Illness
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Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis.

Academic radiology Jan 30, 2019
RATIONALE AND OBJECTIVES: To use machine learning-based magnetic resonance imaging radiomics to predict metachronous liver metastases (MLM) in patients with rectal cancer.
Magnetic Resonance Imaging Rectum Rectal Neoplasms Neoplasm Metastasis Male Humans Middle Aged Algorithms ROC Curve Liver Neoplasms Retrospective Studies Adenocarcinoma Female Support Vector Machine
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Water-fat separation and parameter mapping in cardiac MRI via deep learning with a convolutional neural network.

Journal of magnetic resonance imaging : JMRI Jan 30, 2019
BACKGROUND: Water-fat separation is a postprocessing technique most commonly applied to multiple-gradient-echo magnetic resonance (MR) images to identify fat, provide images with fat suppression, and to measure fat tissue concentration. Recently, Num...
Severity of Illness Index Deep Learning Water Magnetic Resonance Imaging Adipose Tissue Heart Feasibility Studies Myocardial Infarction Image Interpretation, Computer-Assisted Neural Networks, Computer Retrospective Studies Female Male Middle Aged Humans
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