AIMC Topic: Female

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Predicting clinically significant motor function improvement after contemporary task-oriented interventions using machine learning approaches.

Journal of neuroengineering and rehabilitation Sep 29, 2020
BACKGROUND: Accurate prediction of motor recovery after stroke is critical for treatment decisions and planning. Machine learning has been proposed to be a promising technique for outcome prediction because of its high accuracy and ability to process...
Physical Therapy Modalities Stroke Rehabilitation Humans Middle Aged Machine Learning Quality of Life Prognosis ROC Curve Female Recovery of Function Aged Stroke Male
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Using machine learning of clinical data to diagnose COVID-19: a systematic review and meta-analysis.

BMC medical informatics and decision making Sep 29, 2020
BACKGROUND: The recent Coronavirus Disease 2019 (COVID-19) pandemic has placed severe stress on healthcare systems worldwide, which is amplified by the critical shortage of COVID-19 tests.
Sensitivity and Specificity Male Influenza A virus Diagnosis, Differential Influenza, Human Coronavirus Infections COVID-19 Testing Datasets as Topic Clinical Laboratory Techniques Betacoronavirus Pandemics COVID-19 Computer Simulation Female SARS-CoV-2 Humans Pneumonia, Viral Machine Learning
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Artificial intelligence accuracy in detecting pathological breath sounds in children using digital stethoscopes.

Respiratory research Sep 29, 2020
BACKGROUND: Manual auscultation to detect abnormal breath sounds has poor inter-observer reliability. Digital stethoscopes with artificial intelligence (AI) could improve reliable detection of these sounds. We aimed to independently test the abilitie...
Auscultation Respiratory Sounds Reproducibility of Results Male Humans Child, Preschool Artificial Intelligence Child Female Stethoscopes
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Machine Learning-Based Differentiation of Nontuberculous Mycobacteria Lung Disease and Pulmonary Tuberculosis Using CT Images.

BioMed research international Sep 29, 2020
An increasing number of patients infected with nontuberculous mycobacteria (NTM) are observed worldwide. However, it is challenging to identify NTM lung diseases from pulmonary tuberculosis (PTB) due to considerable overlap in classic manifestations ...
Lung Aged Tuberculosis, Pulmonary Adult Nontuberculous Mycobacteria Sensitivity and Specificity Humans Mycobacterium Infections, Nontuberculous Male Machine Learning Middle Aged Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Bronchiectasis Female
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Development and Validation of Machine Learning-Based Prediction for Dependence in the Activities of Daily Living after Stroke Inpatient Rehabilitation: A Decision-Tree Analysis.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Sep 28, 2020
BACKGROUND AND PURPOSE: Accurate prediction using simple and changeable variables is clinically meaningful because some known-predictors, such as stroke severity and patients age cannot be modified with rehabilitative treatment. There are limited cli...
Activities of Daily Living Stroke Rehabilitation Mobility Limitation Clinical Decision Rules Inpatients Decision Trees Recovery of Function Predictive Value of Tests Stroke Male Middle Aged Risk Assessment Treatment Outcome Humans Machine Learning Databases, Factual Female Reproducibility of Results Risk Factors Aged Aged, 80 and over
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Bone age assessment based on deep convolution neural network incorporated with segmentation.

International journal of computer assisted radiology and surgery Sep 28, 2020
PURPOSE: Bone age assessment is not only an important means of assessing maturity of adolescents, but also plays an indispensable role in the fields of orthodontics, kinematics, pediatrics, forensic science, etc. Most studies, however, do not take in...
Bone and Bones X-Rays Adolescent Child, Preschool Child Image Processing, Computer-Assisted Humans Neural Networks, Computer Female Young Adult Male Infant
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The study of the differences between low-functioning autistic children and typically developing children in the processing of the own-race and other-race faces by the machine learning approach.

Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia Sep 28, 2020
OBJECTIVE: Autism spectrum disorder (ASD) is a heterogeneous neurodevelopmental disorder which affects the developmental trajectory in several behavioral domains, including impairments of social communication and stereotyped behavior. Unlike typicall...
Racial Groups Photic Stimulation Facial Recognition Recognition, Psychology Reproducibility of Results Humans Male Machine Learning Child, Preschool Autism Spectrum Disorder Child Female
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Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy.

Physics in medicine and biology Sep 28, 2020
We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features for predicting acute-phase weight loss (WL) in lung cancer radiotherapy. Baseline weight of 388 patients who underwent intensity modulated radiation t...
Machine Learning Algorithms Retrospective Studies Tomography, X-Ray Computed Female Humans Weight Loss Aged Lung Neoplasms Aged, 80 and over Radiographic Image Interpretation, Computer-Assisted Adult Radiotherapy, Intensity-Modulated Male Acute-Phase Reaction Middle Aged
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THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.

Diabetic medicine : a journal of the British Diabetic Association Sep 27, 2020
AIM: To develop and evaluate an artificial intelligence triage system with high sensitivity for detecting referable diabetic retinopathy and maculopathy, while maintaining high specificity for non-referable disease, for clinical implementation within...
Young Adult Triage Adolescent Adult New Zealand Sensitivity and Specificity Algorithms Retina Humans Male Retrospective Studies Implementation Science Middle Aged Female Diabetic Retinopathy Aged Artificial Intelligence Aged, 80 and over Child Image Processing, Computer-Assisted Diabetes Mellitus Mass Screening
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Deep learning algorithms to isolate and quantify the structures of the anterior segment in optical coherence tomography images.

The British journal of ophthalmology Sep 26, 2020
BACKGROUND/AIMS: Accurate isolation and quantification of intraocular dimensions in the anterior segment (AS) of the eye using optical coherence tomography (OCT) images is important in the diagnosis and treatment of many eye diseases, especially angl...
Humans Algorithms Prospective Studies Deep Learning Follow-Up Studies Tomography, Optical Coherence Anterior Eye Segment Glaucoma, Angle-Closure Female Reproducibility of Results Intraocular Pressure Male Middle Aged Gonioscopy
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