AIMC Topic: Retrospective Studies

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Predicting Coronavirus Disease 2019 Infection Risk and Related Risk Drivers in Nursing Homes: A Machine Learning Approach.

Journal of the American Medical Directors Association Aug 27, 2020
OBJECTIVE: Inform coronavirus disease 2019 (COVID-19) infection prevention measures by identifying and assessing risk and possible vectors of infection in nursing homes (NHs) using a machine-learning approach.
Nursing Homes Humans Betacoronavirus Machine Learning Pneumonia, Viral Pandemics COVID-19 Risk Factors Risk Assessment Algorithms United States Forecasting Coronavirus Infections Retrospective Studies SARS-CoV-2
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A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population.

PloS one Aug 27, 2020
Kawasaki disease is the leading cause of pediatric acquired heart disease. Coronary artery abnormalities are the main complication of Kawasaki disease. Kawasaki disease patients with intravenous immunoglobulin resistance are at a greater risk of deve...
Models, Biological Immunoglobulins, Intravenous Drug Resistance Infant Humans Female China Logistic Models Machine Learning Risk Factors Child, Preschool Mucocutaneous Lymph Node Syndrome Retrospective Studies Male ROC Curve Coronary Artery Disease Risk Assessment Feasibility Studies
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ASO Author Reflections: Robotic Radical Hysterectomy for Patients with Early-Stage Cervical Cancer: Oncologic Outcomes.

Annals of surgical oncology Aug 26, 2020
Robotics Neoplasm Staging Laparoscopy Robotic Surgical Procedures Hysterectomy Humans Retrospective Studies Female Uterine Cervical Neoplasms
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Early experience utilizing artificial intelligence shows significant reduction in transfer times and length of stay in a hub and spoke model.

Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences Aug 26, 2020
BACKGROUND: Recently approved artificial intelligence (AI) software utilizes AI powered large vessel occlusion (LVO) detection technology which automatically identifies suspected LVO through CT angiogram (CTA) imaging and alerts on-call stroke teams....
Humans Artificial Intelligence Software Computed Tomography Angiography Length of Stay Retrospective Studies Cerebral Angiography Workflow Female Stroke Aged Time-to-Treatment Male
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Prospective Deployment of Deep Learning in MRI: A Framework for Important Considerations, Challenges, and Recommendations for Best Practices.

Journal of magnetic resonance imaging : JMRI Aug 24, 2020
Artificial intelligence algorithms based on principles of deep learning (DL) have made a large impact on the acquisition, reconstruction, and interpretation of MRI data. Despite the large number of retrospective studies using DL, there are fewer appl...
Reproducibility of Results Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Neural Networks, Computer Artificial Intelligence Algorithms Prospective Studies Retrospective Studies
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Development of Convolutional Neural Networks to identify bone metastasis for prostate cancer patients in bone scintigraphy.

Annals of nuclear medicine Aug 24, 2020
OBJECTIVE: The main aim of this work is to build a robust Convolutional Neural Network (CNN) algorithm that efficiently and quickly classifies bone scintigraphy images, by determining the presence or absence of prostate cancer metastasis.
Image Interpretation, Computer-Assisted Bone and Bones Radionuclide Imaging Humans Retrospective Studies Neural Networks, Computer Male Bone Neoplasms Prostatic Neoplasms
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Automated detection of early-stage ROP using a deep convolutional neural network.

The British journal of ophthalmology Aug 23, 2020
BACKGROUND/AIM: To automatically detect and classify the early stages of retinopathy of prematurity (ROP) using a deep convolutional neural network (CNN).
Humans Neural Networks, Computer Algorithms Retrospective Studies Male Diagnosis, Computer-Assisted ROC Curve Image Processing, Computer-Assisted Female Infant, Newborn Sensitivity and Specificity Cross-Sectional Studies Gestational Age Retinopathy of Prematurity Birth Weight Infant, Premature Infant, Low Birth Weight
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A novel image signature-based radiomics method to achieve precise diagnosis and prognostic stratification of gliomas.

Laboratory investigation; a journal of technical methods and pathology Aug 22, 2020
Radiomics has potential advantages in the noninvasive histopathological and molecular diagnosis of gliomas. We aimed to develop a novel image signature (IS)-based radiomics model to achieve multilayered preoperative diagnosis and prognostic stratific...
Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Deep Learning Adolescent Molecular Diagnostic Techniques Glioma Adult Retrospective Studies Humans Brain Neoplasms Female Prognosis Aged Male Young Adult Middle Aged
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Development and Validation of a Modified Three-Dimensional U-Net Deep-Learning Model for Automated Detection of Lung Nodules on Chest CT Images From the Lung Image Database Consortium and Japanese Datasets.

Academic radiology Aug 21, 2020
RATIONALE AND OBJECTIVES: A more accurate lung nodule detection algorithm is needed. We developed a modified three-dimensional (3D) U-net deep-learning model for the automated detection of lung nodules on chest CT images. The purpose of this study wa...
Deep Learning Lung Neoplasms Japan Humans Retrospective Studies Tomography, X-Ray Computed Lung
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Impact of obesity on surgical and oncologic outcomes in patients with endometrial cancer treated with a robotic approach.

The journal of obstetrics and gynaecology research Aug 20, 2020
AIM: The surgical treatment of endometrial cancer (EC) can be more complicated in obese patients. Robotic surgery could simplify the surgical approach in these patients. The aim of our study was to compare the outcomes of robotic surgery in obese (bo...
Humans Retrospective Studies Laparoscopy Robotic Surgical Procedures Hysterectomy Female Endometrial Neoplasms Postoperative Complications Obesity Robotics
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