AIMC Topic: Cross-Sectional Studies

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Seroprevalence of antibodies for pertussis and diphtheria among people leaving or entering China: a cross-sectional study.

Journal of infection in developing countries May 31, 2019
INTRODUCTION: Despite high population immunity, pertussis remains one of the leading causes of vaccine-preventable deaths worldwide. The aim of this study was to determine the seroprevalence of IgG antibodies to pertussis toxin (PT) and diphtheria am...
Humans Male Travel-Related Illness Immunoglobulin G Middle Aged Whooping Cough Asian People Young Adult Africa China Antibodies, Bacterial Adult Seroepidemiologic Studies Diphtheria Cross-Sectional Studies Employment Pertussis Toxin
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Automated detection of sudden unexpected death in epilepsy risk factors in electronic medical records using natural language processing.

Epilepsia May 21, 2019
OBJECTIVE: Sudden unexpected death in epilepsy (SUDEP) is an important cause of mortality in epilepsy. However, there is a gap in how often providers counsel patients about SUDEP. One potential solution is to electronically prompt clinicians to provi...
Retrospective Studies Electronic Health Records Risk Factors Sensitivity and Specificity Cross-Sectional Studies Natural Language Processing Humans Algorithms Epilepsy, Tonic-Clonic Sudden Unexpected Death in Epilepsy Data Interpretation, Statistical Epilepsy Neurosurgery Drug Resistant Epilepsy Death, Sudden
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Perceptions of drones, digital adherence monitoring technologies and educational videos for tuberculosis control in remote Madagascar: a mixed-method study protocol.

BMJ open May 9, 2019
INTRODUCTION: Poor road and communication infrastructure pose major challenges to tuberculosis (TB) control in many regions of the world. TB surveillance and patient support often fall to community health workers (CHWs) who may lack the time or knowl...
Madagascar Cross-Sectional Studies Male Focus Groups Interviews as Topic Rural Health Services Medication Adherence Clinical Protocols Robotics Health Education Antitubercular Agents Attitude to Health Tuberculosis Telemedicine Video Recording Perception Humans Female Adult
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How Employability Attributes Mediate the Link Between Knowledge Workers' Career Adaptation Concerns and Their Self-Perceived Employability.

Psychological reports May 6, 2019
The study examines employability attributes as psychological mechanisms that explain the link between the career adaptation concerns and self-perceived employability of a sample of professionally qualified knowledge workers (N = 404). A cross-section...
Humans Female Adult Cross-Sectional Studies Knowledge Bases Workforce Motivation Employment Adaptation, Psychological Professional Autonomy Male Middle Aged Surveys and Questionnaires Self Concept South Africa
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Swept source optical coherence tomography to early detect multiple sclerosis disease. The use of machine learning techniques.

PloS one May 6, 2019
OBJECTIVE: To compare axonal loss in ganglion cells detected with swept-source optical coherence tomography (SS-OCT) in eyes of patients with multiple sclerosis (MS) versus healthy controls using different machine learning techniques. To analyze the ...
Tomography, Optical Coherence Early Diagnosis Retinal Ganglion Cells Macula Lutea Multiple Sclerosis, Relapsing-Remitting Adult Cross-Sectional Studies Male Middle Aged Image Processing, Computer-Assisted Humans Machine Learning Female
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Machine learning performance in a microbial molecular autopsy context: A cross-sectional postmortem human population study.

PloS one Apr 15, 2019
BACKGROUND: The postmortem microbiome can provide valuable information to a death investigation and to the human health of the once living. Microbiome sequencing produces, in general, large multi-dimensional datasets that can be difficult to analyze ...
Young Adult Adult Cross-Sectional Studies Autopsy Male High-Throughput Nucleotide Sequencing Middle Aged Time Factors Humans Postmortem Changes Adolescent DNA, Bacterial Datasets as Topic Machine Learning RNA, Ribosomal, 16S DNA, Archaeal Female Sequence Analysis, DNA Aged Microbiota Aged, 80 and over
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Identifying Factors That Affect Patient Survival After Orthotopic Liver Transplant Using Machine-Learning Techniques.

Experimental and clinical transplantation : official journal of the Middle East Society for Organ Transplantation Apr 9, 2019
OBJECTIVES: Survival after liver transplant depends on pretransplant, peritransplant, and posttransplant factors. Identifying effective factors for patient survival after transplant can help transplant centers make better decisions.
Health Status Predictive Value of Tests Liver Transplantation Iran Data Mining Risk Factors Aged Young Adult Adult Humans Cross-Sectional Studies Machine Learning Adolescent Decision Support Techniques Time Factors Retrospective Studies Male Treatment Outcome Female Middle Aged Risk Assessment
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Application of a Neural Network Whole Transcriptome-Based Pan-Cancer Method for Diagnosis of Primary and Metastatic Cancers.

JAMA network open Apr 5, 2019
IMPORTANCE: A molecular diagnostic method that incorporates information about the transcriptional status of all genes across multiple tissue types can strengthen confidence in cancer diagnosis.
Humans Neural Networks, Computer Machine Learning Female Adult Biomarkers, Tumor Cross-Sectional Studies Male Middle Aged Neoplasms Transcriptome Lung Neoplasms Mesothelioma Mesothelioma, Malignant Exome Sequencing
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Machine Learning Approach to find the relation between Endometriosis, benign breast disease, cystitis and non-toxic goiter.

Scientific reports Apr 1, 2019
The exact mechanism of endometriosis is unknown. The recommendation system (RS) based on item similarities of machine learning has never been applied to the relationship between diseases. The study aim was to identify diseases associated with endomet...
Goiter Adult Sensitivity and Specificity Cross-Sectional Studies Middle Aged Adolescent Logistic Models Diagnosis, Differential Endometriosis Fibrocystic Breast Disease Cystitis Humans Machine Learning Female Reproducibility of Results Young Adult
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Validation of a Deep Learning Model to Screen for Glaucoma Using Images from Different Fundus Cameras and Data Augmentation.

Ophthalmology. Glaucoma Apr 1, 2019
PURPOSE: To validate a deep residual learning algorithm to diagnose glaucoma from fundus photography using different fundus cameras at different institutes.
Aged Cross-Sectional Studies Male Deep Learning ROC Curve Humans Glaucoma Algorithms Female Fundus Oculi Optic Disk Fluorescein Angiography
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