AIMC Topic: Cross-Sectional Studies

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Predictive analysis across spatial scales links zoonotic malaria to deforestation.

Proceedings. Biological sciences Jan 16, 2019
The complex transmission ecologies of vector-borne and zoonotic diseases pose challenges to their control, especially in changing landscapes. Human incidence of zoonotic malaria ( Plasmodium knowlesi) is associated with deforestation although mechani...
Plasmodium knowlesi Spatial Analysis Epidemiological Monitoring Zoonoses Forestry Cross-Sectional Studies Humans Animals Models, Statistical Case-Control Studies Machine Learning Remote Sensing Technology Malaria Forests Models, Theoretical Spacecraft Malaysia
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Relationship of the low-density lipoprotein (LDL)/high-density lipoprotein (HDL) index with antioxidant enzymes and with the oxLDL/HDL index.

Gaceta medica de Mexico Jan 1, 2019
INTRODUCTION: The low-density lipoprotein (LDL)/high-density lipoprotein (HDL) index is a predictive factor for atherosclerosis, which is associated with oxidative modifications.
Male Humans Glutathione Peroxidase Oxidative Stress Obesity Female Lipoproteins, HDL Insulin Resistance Nails Adult Lipoproteins, LDL Superoxide Dismutase Smoking Cross-Sectional Studies Magnesium Age Factors Sex Factors
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Accurate Identification of Colonoscopy Quality and Polyp Findings Using Natural Language Processing.

Journal of clinical gastroenterology Jan 1, 2019
OBJECTIVES: The aim of this study was to test the ability of a commercially available natural language processing (NLP) tool to accurately extract examination quality-related and large polyp information from colonoscopy reports with varying report fo...
Humans Female Reproducibility of Results Aged Colonoscopy Aged, 80 and over Predictive Value of Tests Sensitivity and Specificity Natural Language Processing Cross-Sectional Studies Colonic Polyps Male California Middle Aged
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Macular Vessel Density and Ganglion Cell/Inner Plexiform Layer Thickness and Their Combinational Index Using Artificial Intelligence.

Journal of glaucoma Sep 1, 2018
PURPOSE: To evaluate the relationship between macular vessel density and ganglion cell to inner plexiform layer thickness (GCIPLT) and to compare their diagnostic performance. We attempted to develop a new combined parameter using an artificial neura...
Humans Cross-Sectional Studies Intraocular Pressure Male Middle Aged Case-Control Studies Neural Networks, Computer Artificial Intelligence Female Aged Adult Retinal Ganglion Cells Retinal Vessels ROC Curve Glaucoma, Open-Angle Area Under Curve Tomography, Optical Coherence Nerve Fibers
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Man against machine: diagnostic performance of a deep learning convolutional neural network for dermoscopic melanoma recognition in comparison to 58 dermatologists.

Annals of oncology : official journal of the European Society for Medical Oncology Aug 1, 2018
BACKGROUND: Deep learning convolutional neural networks (CNN) may facilitate melanoma detection, but data comparing a CNN's diagnostic performance to larger groups of dermatologists are lacking.
Image Processing, Computer-Assisted Skin Dermatologists International Cooperation Cross-Sectional Studies Deep Learning Clinical Competence ROC Curve Humans Retrospective Studies Melanoma Skin Neoplasms Dermoscopy
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Deep-learning Classifier With an Ultrawide-field Scanning Laser Ophthalmoscope Detects Glaucoma Visual Field Severity.

Journal of glaucoma Jul 1, 2018
PURPOSE: To evaluate the accuracy of detecting glaucoma visual field defect severity using deep-learning (DL) classifier with an ultrawide-field scanning laser ophthalmoscope.
Humans Glaucoma Retrospective Studies Female Deep Learning Cross-Sectional Studies Visual Field Tests Reproducibility of Results Microscopy, Confocal Intraocular Pressure Ophthalmoscopes Aged Vision Disorders Male Adult Image Interpretation, Computer-Assisted Middle Aged Sensitivity and Specificity Visual Fields Severity of Illness Index
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Improving Hip-Worn Accelerometer Estimates of Sitting Using Machine Learning Methods.

Medicine and science in sports and exercise Jul 1, 2018
PURPOSE: This study aimed to improve estimates of sitting time from hip-worn accelerometers used in large cohort studies by using machine learning methods developed on free-living activPAL data.
Accelerometry Sitting Position Hip Survivors Middle Aged Exercise Pilot Projects Thigh Monitoring, Ambulatory Female Aged Breast Neoplasms Cross-Sectional Studies Humans Machine Learning Algorithms
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Examining the Ability of Artificial Neural Networks Machine Learning Models to Accurately Predict Complications Following Posterior Lumbar Spine Fusion.

Spine Jun 15, 2018
STUDY DESIGN: A cross-sectional database study.
Cross-Sectional Studies Male Middle Aged Neural Networks, Computer Lumbar Vertebrae Postoperative Complications Machine Learning Humans Databases, Factual Spinal Fusion Prognosis Female
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The adoption of care robots in home care-A survey on the attitudes of Finnish home care personnel.

Journal of clinical nursing May 1, 2018
AIMS AND OBJECTIVES: This article examines the attitudes of Finnish home care registered nurses, licensed vocational nurses and other health and social care personnel towards the introduction and use of care robots in home care.
Factor Analysis, Statistical Finland Home Care Services Cross-Sectional Studies Humans Male Female Surveys and Questionnaires Aged Attitude of Health Personnel Robotics
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Prediction of Abnormal Myocardial Relaxation From Signal Processed Surface ECG.

Journal of the American College of Cardiology Apr 17, 2018
BACKGROUND: Myocardial relaxation is impaired in almost all cases with left ventricular diastolic dysfunction (LVDD) and is a strong predictor of cardiovascular and all-cause mortality.
Humans Ventricular Dysfunction, Left Cross-Sectional Studies Machine Learning Male Prospective Studies Diastole Female Middle Aged Electrocardiography Aged Heart
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