AIMC Topic: Physical Examination

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Risk of a second wave of Covid-19 infections: using artificial intelligence to investigate stringency of physical distancing policies in North America.

International orthopaedics Jun 5, 2020
PURPOSE: Accurately forecasting the occurrence of future covid-19-related cases across relaxed (Sweden) and stringent (USA and Canada) policy contexts has a renewed sense of urgency. Moreover, there is a need for a multidimensional county-level appro...
COVID-19 SARS-CoV-2 Sweden Risk Factors Humans Artificial Intelligence Pandemics Telemedicine Physical Examination Physical Distancing Betacoronavirus Pneumonia, Viral Canada United States Bayes Theorem Coronavirus Infections
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Artificial intelligence for teleophthalmology-based diabetic retinopathy screening in a national programme: an economic analysis modelling study.

The Lancet. Digital health Apr 23, 2020
BACKGROUND: Deep learning is a novel machine learning technique that has been shown to be as effective as human graders in detecting diabetic retinopathy from fundus photographs. We used a cost-minimisation analysis to evaluate the potential savings ...
Humans Diabetic Retinopathy Artificial Intelligence Machine Learning Physical Examination Ophthalmology Singapore Models, Biological Retina Diagnostic Techniques, Ophthalmological Health Care Costs Photography Telemedicine Cost-Benefit Analysis Image Processing, Computer-Assisted Diabetes Mellitus Mass Screening Decision Trees Aged Adult Sensitivity and Specificity Middle Aged
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Cancer Prevention Using Machine Learning, Nudge Theory and Social Impact Bond.

International journal of environmental research and public health Jan 28, 2020
There have been prior attempts to utilize machine learning to address issues in the medical field, particularly in diagnoses using medical images and developing therapeutic regimens. However, few cases have demonstrated the usefulness of machine lear...
Humans Machine Learning Tokyo Colorectal Neoplasms Early Detection of Cancer Physical Examination Social Change
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Subgrouping Factors Influencing Migraine Intensity in Women: A Semi-automatic Methodology Based on Machine Learning and Information Geometry.

Pain practice : the official journal of World Institute of Pain Dec 2, 2019
BACKGROUND: Migraine is a heterogeneous condition with multiple clinical manifestations. Machine learning algorithms permit the identification of population groups, providing analytical advantages over other modeling techniques.
Disability Evaluation Physical Examination Female Adult Middle Aged Migraine Disorders Humans Machine Learning
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Human Versus Machine: Comparing a Deep Learning Algorithm to Human Gradings for Detecting Glaucoma on Fundus Photographs.

American journal of ophthalmology Nov 12, 2019
PURPOSE: To compare the diagnostic performance of human gradings vs predictions provided by a machine-to-machine (M2M) deep learning (DL) algorithm trained to quantify retinal nerve fiber layer (RNFL) damage on fundus photographs.
Visual Field Tests Optic Nerve Diseases Photography Physical Examination Glaucoma, Open-Angle Gonioscopy Fundus Oculi Nerve Fibers Retinal Ganglion Cells Visual Fields ROC Curve Vision Disorders Area Under Curve Tomography, Optical Coherence Algorithms Retrospective Studies Humans Male Female Middle Aged Aged Cross-Sectional Studies Deep Learning Intraocular Pressure
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Bone age assessment with various machine learning techniques: A systematic literature review and meta-analysis.

PloS one Jul 25, 2019
BACKGROUND: The assessment of bone age and skeletal maturity and its comparison to chronological age is an important task in the medical environment for the diagnosis of pediatric endocrinology, orthodontics and orthopedic disorders, and legal enviro...
Age Determination by Skeleton Bone Development Humans History, 21st Century Machine Learning History, 20th Century Child Child Development Age Factors Physical Examination
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A Deep Learning Approach for Automated Detection of Geographic Atrophy from Color Fundus Photographs.

Ophthalmology Jun 11, 2019
PURPOSE: To assess the utility of deep learning in the detection of geographic atrophy (GA) from color fundus photographs and to explore potential utility in detecting central GA (CGA).
Humans Female Reproducibility of Results Aged Aged, 80 and over Sensitivity and Specificity Male Middle Aged Deep Learning Photography Image Processing, Computer-Assisted Physical Examination Area Under Curve Geographic Atrophy Diagnostic Techniques, Ophthalmological
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A pilot study of autonomous artificial intelligence-based diabetic retinopathy screening in Poland.

Acta ophthalmologica May 3, 2019
Mass Screening Retina Physical Examination Vision Screening Artificial Intelligence Poland Diagnosis, Computer-Assisted Humans Pilot Projects Diabetic Retinopathy
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Deep Learning Algorithms with Demographic Information Help to Detect Tuberculosis in Chest Radiographs in Annual Workers' Health Examination Data.

International journal of environmental research and public health Jan 16, 2019
We aimed to use deep learning to detect tuberculosis in chest radiographs in annual workers' health examination data and compare the performances of convolutional neural networks (CNNs) based on images only (I-CNN) and CNNs including demographic vari...
Adult Sensitivity and Specificity Male Middle Aged Occupational Health Physical Examination Deep Learning Demography Humans ROC Curve Female Radiography Tuberculosis, Pulmonary
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Alzheimer's disease and driving: review of the literature and consensus guideline from Belgian dementia experts and the Belgian road safety institute endorsed by the Belgian Medical Association.

Acta neurologica Belgica Oct 5, 2017
Alzheimer's disease (AD) is a highly prevalent condition and its prevalence is expected to further increase due to the aging of the general population. It is obvious that the diagnosis of AD has implications for driving. Finally, driving discussions ...
Belgium Humans Neuropsychological Tests Alzheimer Disease Behavior Automobile Driving Physical Examination Guidelines as Topic
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