AIMC Topic: Asthma

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Associations between trees and grass presence with childhood asthma prevalence using deep learning image segmentation and a novel green view index.

Environmental pollution (Barking, Essex : 1987) Jun 14, 2021
Limitations of Normalized Difference Vegetation Index (NDVI) potentially contributed to the inconsistent findings of greenspace exposure and childhood asthma. The aim of this study was to use a novel greenness exposure assessment method, capable of o...
Trees Asthma Particulate Matter Cross-Sectional Studies Environmental Exposure Prevalence Poaceae Air Pollutants Air Pollution Deep Learning Child Humans
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Does machine learning have a role in the prediction of asthma in children?

Paediatric respiratory reviews Jun 9, 2021
Asthma is the most common chronic lung disease in childhood. There has been a significant worldwide effort to develop tools/methods to identify children's risk for asthma as early as possible for preventative and early management strategies. Unfortun...
Humans Machine Learning Asthma Child
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Design Comorbidity Portfolios to Improve Treatment Cost Prediction of Asthma Using Machine Learning.

IEEE journal of biomedical and health informatics Jun 3, 2021
Comorbidity is an important factor to consider when trying to predict the cost of treating asthma patients. When an asthmatic patient suffered from comorbidity, the cost of treating such a patient becomes dependent on the nature of the comorbidity. T...
Machine Learning Asthma Comorbidity Health Care Costs Humans Neural Networks, Computer
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Artificial Intelligence and Machine Learning in Chronic Airway Diseases: Focus on Asthma and Chronic Obstructive Pulmonary Disease.

International journal of medical sciences Jun 1, 2021
Chronic airway diseases are characterized by airway inflammation, obstruction, and remodeling and show high prevalence, especially in developing countries. Among them, asthma and chronic obstructive pulmonary disease (COPD) show the highest morbidity...
Data Mining Pulmonary Disease, Chronic Obstructive Asthma Models, Biological Humans Machine Learning Clinical Decision-Making
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Prioritizing Molecular Biomarkers in Asthma and Respiratory Allergy Using Systems Biology.

Frontiers in immunology Apr 15, 2021
Highly prevalent respiratory diseases such as asthma and allergy remain a pressing health challenge. Currently, there is an unmet need for precise diagnostic tools capable of predicting the great heterogeneity of these illnesses. In a previous study ...
Humans Neural Networks, Computer Systems Biology Models, Theoretical Biomarkers Hypersensitivity Asthma
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Predictors of 30-Day Mortality Among Dutch Patients Undergoing Colorectal Cancer Surgery, 2011-2016.

JAMA network open Apr 1, 2021
IMPORTANCE: Quality improvement programs for colorectal cancer surgery have been introduced with benchmarking based on quality indicators, such as mortality. Detailed (pre)operative characteristics may offer relevant information for proper case-mix c...
Colorectal Neoplasms Male Middle Aged Comorbidity Aged, 80 and over Pulmonary Disease, Chronic Obstructive Asthma Support Vector Machine Area Under Curve Laparoscopy Myocardial Infarction Length of Stay Logistic Models Hypertension Humans Machine Learning Risk Factors Aged Intensive Care Units Female Multivariate Analysis Netherlands Mortality Patient Readmission Colectomy
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Machine learning in asthma research: moving toward a more integrated approach.

Expert review of respiratory medicine Mar 16, 2021
: Big data are reshaping the future of medicine. The growing availability and increasing complexity of data have favored the adoption of modern analytical and computational methodologies in every area of medicine. Over the past decades, asthma resear...
Asthma Humans Machine Learning
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Personalized prediction of early childhood asthma persistence: A machine learning approach.

PloS one Mar 1, 2021
Early childhood asthma diagnosis is common; however, many children diagnosed before age 5 experience symptom resolution and it remains difficult to identify individuals whose symptoms will persist. Our objective was to develop machine learning models...
Prognosis Electronic Health Records Asthma Humans Eczema Machine Learning Child, Preschool Rhinitis, Allergic Probability
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Asthma-prone areas modeling using a machine learning model.

Scientific reports Jan 21, 2021
Nowadays, owing to population growth, increasing environmental pollution, and lifestyle changes, the number of asthmatics has significantly increased. Therefore, the purpose of our study was to determine the asthma-prone areas in Tehran, Iran conside...
Humans Sulfur Dioxide Machine Learning Vehicle Emissions Female Humidity Nitrogen Dioxide Air Pollutants Air Pollution Ozone Particulate Matter Environmental Exposure Iran Temperature Adolescent Carbon Monoxide Asthma Child Male Environmental Monitoring
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Novel Machine Learning Can Predict Acute Asthma Exacerbation.

Chest Jan 10, 2021
BACKGROUND: Asthma exacerbations result in significant health and economic burden, but are difficult to predict.
Ohio Adolescent Female Humans Aged Machine Learning Aged, 80 and over Male Electronic Health Records Adult Middle Aged Asthma Predictive Value of Tests Symptom Flare Up
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