AIMC Topic: Age Factors

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Machine learning based classification of cells into chronological stages using single-cell transcriptomics.

Scientific reports Nov 21, 2018
Age-associated deterioration of cellular physiology leads to pathological conditions. The ability to detect premature aging could provide a window for preventive therapies against age-related diseases. However, the techniques for determining cellular...
Single-Cell Analysis Age Factors Cytological Techniques Zebrafish Insulin-Secreting Cells Humans Machine Learning Animals Gene Expression Profiling
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Predicting the risk of emergency admission with machine learning: Development and validation using linked electronic health records.

PLoS medicine Nov 20, 2018
BACKGROUND: Emergency admissions are a major source of healthcare spending. We aimed to derive, validate, and compare conventional and machine learning models for prediction of the first emergency admission. Machine learning methods are capable of ca...
Age Factors Emergency Service, Hospital Data Mining Sex Factors Health Services Needs and Demand Risk Assessment Patient Admission England Needs Assessment Adolescent Aged, 80 and over Time Factors Humans Young Adult Socioeconomic Factors Health Status Machine Learning Adult Male Electronic Health Records Middle Aged Female Reproducibility of Results Risk Factors Aged
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Predominant polarity classification and associated clinical variables in bipolar disorder: A machine learning approach.

Journal of affective disorders Nov 6, 2018
BACKGROUND: Bipolar disorder (BD) is a severe psychiatric disorder characterized by periodic episodes of manic and depressive symptomatology. Predominant polarity (PP) appears to be an important specifier of BD. The present study employed machine lea...
Bipolar Disorder Cohort Studies ROC Curve Age Factors Substance-Related Disorders Area Under Curve Hospitalization Adult Cross-Sectional Studies Male Middle Aged Alcoholism Tobacco Use Disorder Demography Feeding and Eating Disorders Hallucinations Delusions Humans Machine Learning Algorithms Female
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Prediction of myopia development among Chinese school-aged children using refraction data from electronic medical records: A retrospective, multicentre machine learning study.

PLoS medicine Nov 6, 2018
BACKGROUND: Electronic medical records provide large-scale real-world clinical data for use in developing clinical decision systems. However, sophisticated methodology and analytical skills are required to handle the large-scale datasets necessary fo...
Humans Machine Learning Prognosis Retrospective Studies Electronic Health Records Female Age Factors Myopia Reproducibility of Results Predictive Value of Tests Diagnosis, Computer-Assisted Young Adult Data Mining China Male Adolescent Disease Progression Time Factors Refraction, Ocular Child
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A unified non-linear approach based on recurrence quantification analysis and approximate entropy: application to the classification of heart rate variability of age-stratified subjects.

Medical & biological engineering & computing Nov 3, 2018
This paper presents a unified approach based on the recurrence quantification analysis (RQA) and approximate entropy (ApEn) for the classification of heart rate variability (HRV). In this paper, the optimum tolerance threshold (r) corresponding to Ap...
Data Interpretation, Statistical Heart Rate Nonlinear Dynamics Entropy Models, Cardiovascular Humans Neural Networks, Computer Databases, Factual Aged Aged, 80 and over Adult Middle Aged Support Vector Machine Age Factors
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A Deep Automated Skeletal Bone Age Assessment Model with Heterogeneous Features Learning.

Journal of medical systems Nov 3, 2018
Skeletal bone age assessment is a widely used standard procedure in both disease detection and growth prediction for children in endocrinology. Conventional manual assessment methods mainly rely on personal experience in observing X-ray images of lef...
Humans Neural Networks, Computer Algorithms Age Factors Female Wrist Infant, Newborn Hand Male Infant Sex Factors Adolescent Racial Groups Child, Preschool Age Determination by Skeleton Child Image Processing, Computer-Assisted Support Vector Machine
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[Hepatitis B and renal failure: prevalence and associated factors in National University Hospital Center of Cotonou].

The Pan African medical journal Oct 17, 2018
INTRODUCTION: the association between the kidneys and hepatitis B is complex. This study aims to determine the prevalence and factors associated with renal disease in people living with hepatitis B virus (PLHBV) in Cotonou.
Antiviral Agents Hepatitis B Hypertension Glomerular Filtration Rate Tenofovir Adult Age Factors Cross-Sectional Studies Hepatitis B Surface Antigens Male Hospitals, University Humans Middle Aged Benin Female Prevalence Renal Insufficiency Risk Factors Adolescent Aged Young Adult
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Comfort and Attitudes Towards Robots Among Young, Middle-Aged, and Older Adults: A Cross-Sectional Study.

Journal of nursing scholarship : an official publication of Sigma Theta Tau International Honor Society of Nursing Sep 19, 2018
PURPOSE: To explore the social impact of, comfort with, and negative attitudes towards robots among young, middle-aged, and older adults in the United States.
Humans Female Aged Aged, 80 and over Young Adult Adult Cross-Sectional Studies Robotics Male Attitude Middle Aged Surveys and Questionnaires Adolescent Age Factors
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Demographic and Symptomatic Features of Voice Disorders and Their Potential Application in Classification Using Machine Learning Algorithms.

Folia phoniatrica et logopaedica : official organ of the International Association of Logopedics and Phoniatrics (IALP) Sep 5, 2018
BACKGROUND: Studies have used questionnaires of dysphonic symptoms to screen voice disorders. This study investigated whether the differential presentation of demographic and symptomatic features can be applied to computerized classification.
Adult Male Vocal Cord Paralysis Middle Aged Humans Sex Factors Neural Networks, Computer Severity of Illness Index Voice Disorders Smoking Algorithms Age Factors Laryngeal Neoplasms Alcohol Drinking Retrospective Studies Supervised Machine Learning Voice Quality Symptom Assessment Female Glottis Wounds and Injuries Aged Demography
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Assessment of the Feasibility of automated, real-time clinical decision support in the emergency department using electronic health record data.

BMC emergency medicine Jul 3, 2018
BACKGROUND: The use of big data and machine learning within clinical decision support systems (CDSSs) has the potential to transform medicine through better prognosis, diagnosis and automation of tasks. Real-time application of machine learning algor...
Emergency Service, Hospital Documentation Vital Signs Racial Groups Male Humans Middle Aged Severity of Illness Index Machine Learning Time Factors Electronic Health Records Decision Support Systems, Clinical Female Age Factors Reproducibility of Results Risk Factors
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