AIMC Topic:
Cross-Sectional Studies

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Screening Candidates for Refractive Surgery With Corneal Tomographic-Based Deep Learning.

JAMA ophthalmology May 1, 2020
IMPORTANCE: Evaluating corneal morphologic characteristics with corneal tomographic scans before refractive surgery is necessary to exclude patients with at-risk corneas and keratoconus. In previous studies, researchers performed screening with machi...
Female Young Adult Adult Cross-Sectional Studies Humans Artificial Intelligence Machine Learning Algorithms Models, Theoretical Keratoconus Corneal Topography Refractive Surgical Procedures Tomography Male Deep Learning China ROC Curve
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Strategies for controlling violence against health care workers: Application of fuzzy analytical hierarchy process and fuzzy additive ratio assessment.

Journal of nursing management May 1, 2020
OBJECTIVE: The present study aimed to identify and prioritize control measures of violence against health care workers (HWs) using the fuzzy analytical hierarchy process (FAHP) and fuzzy additive ratio assessment (ARAS-F).
Humans Cross-Sectional Studies Risk Assessment Qualitative Research Fuzzy Logic Analytic Hierarchy Process Workplace Violence
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Assessment of a Segmentation-Free Deep Learning Algorithm for Diagnosing Glaucoma From Optical Coherence Tomography Scans.

JAMA ophthalmology Apr 1, 2020
IMPORTANCE: Conventional segmentation of the retinal nerve fiber layer (RNFL) is prone to errors that may affect the accuracy of spectral-domain optical coherence tomography (SD-OCT) scans in detecting glaucomatous damage.
Humans Algorithms Female Intraocular Pressure Male Middle Aged Deep Learning Aged Aged, 80 and over Adult Cross-Sectional Studies Visual Fields Slit Lamp Microscopy Visual Field Tests Glaucoma, Open-Angle Gonioscopy ROC Curve Tomography, Optical Coherence Nerve Fibers Retinal Ganglion Cells
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Medios- An offline, smartphone-based artificial intelligence algorithm for the diagnosis of diabetic retinopathy.

Indian journal of ophthalmology Feb 1, 2020
PURPOSE: An observational study to assess the sensitivity and specificity of the Medios smartphone-based offline deep learning artificial intelligence (AI) software to detect diabetic retinopathy (DR) compared with the image diagnosis of ophthalmolog...
Middle Aged Smartphone Mass Screening Female Reproducibility of Results Cross-Sectional Studies Male Diabetic Retinopathy Artificial Intelligence Software Algorithms Humans
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Characterization of Central Visual Field Loss in End-stage Glaucoma by Unsupervised Artificial Intelligence.

JAMA ophthalmology Feb 1, 2020
IMPORTANCE: Although the central visual field (VF) in end-stage glaucoma may substantially vary among patients, structure-function studies and quality-of-life assessments are impeded by the lack of appropriate characterization of end-stage VF loss.
Visual Fields Aged, 80 and over Cross-Sectional Studies Middle Aged Longitudinal Studies Humans Glaucoma Artificial Intelligence Retrospective Studies Aged
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Utility of MemTrax and Machine Learning Modeling in Classification of Mild Cognitive Impairment.

Journal of Alzheimer's disease : JAD Jan 1, 2020
BACKGROUND: The widespread incidence and prevalence of Alzheimer's disease and mild cognitive impairment (MCI) has prompted an urgent call for research to validate early detection cognitive screening and assessment.
Models, Psychological Mental Status and Dementia Tests Male Humans Middle Aged Machine Learning Cognitive Dysfunction Female Neuropsychological Tests Aged Cross-Sectional Studies
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Effects of robot-assisted gait training alongside conventional therapy on the development of walking in children with cerebral palsy.

Journal of pediatric rehabilitation medicine Jan 1, 2020
PURPOSE: To investigate the effects of robot-assisted gait training (RAGT) alongside conventional therapy on the standing and walking abilities of children with cerebral palsy (CP).
Humans Physical Therapy Modalities Female Gait Cross-Sectional Studies Child Walk Test Cerebral Palsy Male Treatment Outcome Standing Position Adolescent Robotics Orthotic Devices Child, Preschool Walking
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Obtaining dual-energy computed tomography (CT) information from a single-energy CT image for quantitative imaging analysis of living subjects by using deep learning.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2020
Computed tomographic (CT) is a fundamental imaging modality to generate cross-sectional views of internal anatomy in a living subject or interrogate material composition of an object, and it has been routinely used in clinical applications and nondes...
Humans Tomography, X-Ray Computed Cross-Sectional Studies Deep Learning Computational Biology
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Vitamin D deficiency among children aged 10-18 years in Sri Lanka.

The Ceylon medical journal Dec 31, 2019
BACKGROUND: Vitamin D deficiency (VDD) and insufficiency (VDI) are public health problems in many countries, and limited data is available on the prevalence of VDD/VDI in Sri Lanka.
Male Diet Prevalence Adolescent Humans Child Nutritional Status Female Vitamin D Climate Risk Factors Vitamin D Deficiency Diet Surveys Cross-Sectional Studies Sri Lanka
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Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.

JAMA ophthalmology Dec 1, 2019
IMPORTANCE: A deep learning system (DLS) that could automatically detect glaucomatous optic neuropathy (GON) with high sensitivity and specificity could expedite screening for GON.
Male Humans Deep Learning ROC Curve Databases, Factual Area Under Curve Diagnostic Techniques, Ophthalmological Predictive Value of Tests Female Fundus Oculi Photography Sensitivity and Specificity Optic Nerve Diseases Glaucoma, Open-Angle Cross-Sectional Studies False Positive Reactions
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