AIMC Topic: Aged, 80 and over

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Machine Learning Approaches for Fracture Risk Assessment: A Comparative Analysis of Genomic and Phenotypic Data in 5130 Older Men.

Calcified tissue international Jul 29, 2020
The study aims were to develop fracture prediction models by using machine learning approaches and genomic data, as well as to identify the best modeling approach for fracture prediction. The genomic data of Osteoporotic Fractures in Men, cohort Stud...
Aged Aged, 80 and over Male Risk Assessment Cohort Studies Humans Machine Learning Phenotype Bone Density Genomics Fractures, Bone Activities of Daily Living
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Validation of the usefulness of artificial neural networks for risk prediction of adverse drug reactions used for individual patients in clinical practice.

PloS one Jul 29, 2020
Artificial neural networks are the main tools for data mining and were inspired by the human brain and nervous system. Studies have demonstrated their usefulness in medicine. However, no studies have used artificial neural networks for the prediction...
Middle Aged Risk Assessment Humans Aged Adolescent Models, Statistical Aged, 80 and over Neural Networks, Computer Drug-Related Side Effects and Adverse Reactions Kidney Prognosis Young Adult Vancomycin Logistic Models Retrospective Studies Adult Analysis of Variance Female Male
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Application of artificial intelligence using a convolutional neural network for diagnosis of early gastric cancer based on magnifying endoscopy with narrow-band imaging.

Journal of gastroenterology and hepatology Jul 28, 2020
BACKGROUND AND AIM: Magnifying endoscopy with narrow-band imaging (ME-NBI) has made a huge contribution to clinical practice. However, acquiring skill at ME-NBI diagnosis of early gastric cancer (EGC) requires considerable expertise and experience. R...
Humans Neural Networks, Computer Artificial Intelligence Male Female Middle Aged Early Detection of Cancer Aged Predictive Value of Tests Aged, 80 and over Endoscopy, Gastrointestinal Adult Narrow Band Imaging Stomach Neoplasms Sensitivity and Specificity
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Identifying prostate cancer and its clinical risk in asymptomatic men using machine learning of high dimensional peripheral blood flow cytometric natural killer cell subset phenotyping data.

eLife Jul 28, 2020
We demonstrate that prostate cancer can be identified by flow cytometric profiling of blood immune cell subsets. Herein, we profiled natural killer (NK) cell subsets in the blood of 72 asymptomatic men with Prostate-Specific Antigen (PSA) levels < 20...
Killer Cells, Natural Asymptomatic Diseases Blood Circulation Diagnostic Techniques, Urological Risk Assessment Prostatic Neoplasms Prostate-Specific Antigen Flow Cytometry Practice Guidelines as Topic Humans Machine Learning Aged Aged, 80 and over Male Middle Aged
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Validation of Deep-Learning Image Reconstruction for Low-Dose Chest Computed Tomography Scan: Emphasis on Image Quality and Noise.

Korean journal of radiology Jul 27, 2020
OBJECTIVE: Iterative reconstruction degrades image quality. Thus, further advances in image reconstruction are necessary to overcome some limitations of this technique in low-dose computed tomography (LDCT) scan of the chest. Deep-learning image reco...
Humans Retrospective Studies Tomography, X-Ray Computed Female Aged Aged, 80 and over Male Middle Aged Deep Learning Thorax Lung Neoplasms Early Detection of Cancer Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Signal-To-Noise Ratio
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Prediction of 1-Year Mortality from Acute Myocardial Infarction Using Machine Learning.

The American journal of cardiology Jul 26, 2020
Risk stratification at hospital discharge could be instrumental in guiding postdischarge care. In this study, the risk models for 1-year mortality using machine learning (ML) were evaluated for guiding management of acute myocardial infarction (AMI) ...
Myocardial Infarction Machine Learning Time Factors Algorithms ROC Curve Aged Republic of Korea Logistic Models Aged, 80 and over Female Predictive Value of Tests Male Risk Factors Registries Humans Middle Aged Risk Assessment
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Early Prediction of Acute Kidney Injury in the Emergency Department With Machine-Learning Methods Applied to Electronic Health Record Data.

Annals of emergency medicine Jul 24, 2020
STUDY OBJECTIVE: Acute kidney injury occurs commonly and is a leading cause of prolonged hospitalization, development and progression of chronic kidney disease, and death. Early acute kidney injury treatment can improve outcomes. However, current dec...
Humans Aged Aged, 80 and over Adult Cross-Sectional Studies Male Machine Learning Retrospective Studies Acute Kidney Injury Electronic Health Records Female Middle Aged Adolescent Emergency Service, Hospital Creatinine Clinical Decision Rules
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A promising approach for screening pulmonary hypertension based on frontal chest radiographs using deep learning: A retrospective study.

PloS one Jul 24, 2020
BACKGROUND: To date, the missed diagnosis rate of pulmonary hypertension (PH) was high, and there has been limited development of a rapid, simple, and effective way to screen the disease. The purpose of this study is to develop a deep learning approa...
Male Middle Aged Deep Learning China Mass Screening Humans Retrospective Studies Radiographic Image Interpretation, Computer-Assisted Female Hypertension, Pulmonary Aged Thorax Aged, 80 and over Mass Chest X-Ray Adult
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Phase I trial on robot assisted retinal vein cannulation with ocriplasmin infusion for central retinal vein occlusion.

Acta ophthalmologica Jul 23, 2020
PURPOSE: To evaluate the safety and feasibility of robot-assisted retinal vein cannulation with Ocriplasmin infusion for central retinal vein occlusion.
Retinal Vein Occlusion Fluorescein Angiography Vitrectomy Catheterization Fibrinolysin Retinal Vein Infusions, Intravenous Male Humans Robotics Middle Aged Prospective Studies Tomography, Optical Coherence Treatment Outcome Female Peptide Fragments Follow-Up Studies Aged Fundus Oculi Visual Acuity Aged, 80 and over
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The effect of deep convolutional neural networks on radiologists' performance in the detection of hip fractures on digital pelvic radiographs.

European journal of radiology Jul 23, 2020
PURPOSE: The purpose of our study is to develop deep convolutional neural network (DCNN) for detecting hip fractures using CT and MRI as a gold standard, and to evaluate the diagnostic performance of 7 readers with and without DCNN.
Pelvis Hip Fractures Radiographic Image Enhancement Radiography, Abdominal Deep Learning Humans ROC Curve Neural Networks, Computer Image Processing, Computer-Assisted Tomography, X-Ray Computed Magnetic Resonance Imaging Female Area Under Curve Aged Aged, 80 and over Male Middle Aged
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