AIMC Topic: Asthma

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Asthma Exacerbation Prediction and Risk Factor Analysis Based on a Time-Sensitive, Attentive Neural Network: Retrospective Cohort Study.

Journal of medical Internet research Jul 31, 2020
BACKGROUND: Asthma exacerbation is an acute or subacute episode of progressive worsening of asthma symptoms and can have a significant impact on patients' quality of life. However, efficient methods that can help identify personalized risk factors an...
Quality of Life Disease Progression Deep Learning Humans Neural Networks, Computer Retrospective Studies Female Risk Factors Asthma Male Risk Assessment
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Predicting the risk of asthma attacks in children, adolescents and adults: protocol for a machine learning algorithm derived from a primary care-based retrospective cohort.

BMJ open Jul 23, 2020
INTRODUCTION: Most asthma attacks and subsequent deaths are potentially preventable. We aim to develop a prognostic tool for identifying patients at high risk of asthma attacks in primary care by leveraging advances in machine learning.
Machine Learning Algorithms Retrospective Studies Aged Humans Risk Factors Asthma Aged, 80 and over Adolescent Middle Aged Young Adult Child Adult Primary Health Care
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Pulmonary Embolism in Acute Asthma Exacerbation: Clinical Characteristics, Prediction Model and Hospital Outcomes.

Lung May 18, 2020
PURPOSE: Little is known about the characteristics and impact of acute pulmonary embolism (PE) during episodes of asthma exacerbation. We aimed to characterize patients diagnosed with acute PE in the setting of asthma exacerbation, develop a predicti...
Fibrin Fibrinogen Degradation Products Computed Tomography Angiography Clinical Decision Rules Body Mass Index Oxygen International Normalized Ratio Disease Progression Pulmonary Embolism Intensive Care Units Comorbidity Creatinine Female Case-Control Studies Adult Hospitals, University Aged Length of Stay Asthma Heart Rate Humans Male Natriuretic Peptide, Brain Machine Learning Middle Aged
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Diagnosis of Asthma Based on Routine Blood Biomarkers Using Machine Learning.

Computational intelligence and neuroscience May 14, 2020
Intelligent medical diagnosis has become common in the era of big data, although this technique has been applied to asthma only in limited contexts. Using routine blood biomarkers to identify asthma patients would make clinical diagnosis easier to im...
ROC Curve Lymphocyte Count Humans Machine Learning Biomarkers Asthma
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Predicting polysomnographic severity thresholds in children using machine learning.

Pediatric research May 9, 2020
BACKGROUND: Approximately 500,000 children undergo tonsillectomy and adenoidectomy (T&A) annually for treatment of obstructive sleep disordered breathing (oSDB). Although polysomnography is beneficial for preoperative risk stratification in these chi...
Machine Learning Algorithms Female Asthma Humans Decision Making Tonsillectomy Signal Processing, Computer-Assisted Sleep Apnea Syndromes Male Surveys and Questionnaires Child Monitoring, Physiologic Hypersensitivity Sleep Apnea, Obstructive Polysomnography Anthropometry Oximetry Risk Adenoidectomy Actigraphy
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Feature engineering with clinical expert knowledge: A case study assessment of machine learning model complexity and performance.

PloS one Apr 23, 2020
Incorporating expert knowledge at the time machine learning models are trained holds promise for producing models that are easier to interpret. The main objectives of this study were to use a feature engineering approach to incorporate clinical exper...
Prognosis Asthma Health Knowledge, Attitudes, Practice Humans Machine Learning
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Deep learning approaches for sleep disorder prediction in an asthma cohort.

The Journal of asthma : official journal of the Association for the Care of Asthma Mar 18, 2020
OBJECTIVE: Sleep is a natural activity of humans that affects physical and mental health; therefore, sleep disturbance may lead to fatigue and lower productivity. This study examined 1 million samples included in the Taiwan National Health Insurance ...
Humans Artificial Intelligence Female Young Adult Adult Nerve Tissue Proteins Predictive Value of Tests DNA-Binding Proteins Deep Learning Sleep Wake Disorders Asthma Adolescent Male Child, Preschool Middle Aged Child Infant
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A modern approach to identifying and characterizing child asthma and wheeze phenotypes based on clinical data.

PloS one Dec 30, 2019
'Asthma' is a complex disease that encapsulates a heterogeneous group of phenotypes and endotypes. Research to understand these phenotypes has previously been based on longitudinal wheeze patterns or hypothesis-driven observational criteria. The aim ...
Respiratory Sounds Male Female Twins Severity of Illness Index Humans Regression Analysis Sweden Diseases in Twins Adolescent Machine Learning Eosinophils Risk Factors Child Data Analysis Medical History Taking Asthma Biomarkers Leukocyte Count
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The doctor will see you now: How machine learning and artificial intelligence can extend our understanding and treatment of asthma.

The Journal of allergy and clinical immunology Dec 25, 2019
Physicians Asthma Allergy and Immunology Humans Immunologic Techniques Machine Learning
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Machine learning approach to single nucleotide polymorphism-based asthma prediction.

PloS one Dec 4, 2019
Machine learning (ML) is poised as a transformational approach uniquely positioned to discover the hidden biological interactions for better prediction and diagnosis of complex diseases. In this work, we integrated ML-based models for feature selecti...
Machine Learning Asthma ROC Curve Polymorphism, Single Nucleotide Humans Models, Theoretical Support Vector Machine
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