AIMC Topic: Rhinitis, Allergic
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Prediction of outpatient visits for allergic rhinitis using an artificial intelligence LSTM model - a study in Eastern China.
BMC public health
Apr 9, 2025
BACKGROUND: Allergic rhinitis is a common disease that can affect the health of patients and bring huge social and economic burdens. In this study, we developed a model to predict the incidence rate of allergic rhinitis so as to provide accurate info...
In-silico exploring pathway and mechanism-based therapeutics for allergic rhinitis: Network pharmacology, molecular docking, ADMET, quantum chemistry and machine learning based QSAR approaches.
Computers in biology and medicine
Feb 4, 2025
Allergic rhinitis is a devastating health complication that interrupts the quality of daily life and significantly affects around 40 % of the population worldwide. Despite the availability of various treatment options, many patients continue to strug...
Interpretable machine learning for allergic rhinitis prediction among preschool children in Urumqi, China.
Scientific reports
Sep 27, 2024
This study aimed to investigate the advantages and applications of machine learning models in predicting the risk of allergic rhinitis (AR) in children aged 2-8, compared to traditional logistic regression. The study analyzed questionnaire data from ...
Artificial Intelligence-Supported Development of Health Guideline Questions.
Annals of internal medicine
Sep 24, 2024
BACKGROUND: Guideline questions are typically proposed by experts.
Concepts for the Development of Person-Centered, Digitally Enabled, Artificial Intelligence-Assisted ARIA Care Pathways (ARIA 2024).
The journal of allergy and clinical immunology. In practice
Jul 4, 2024
The traditional healthcare model is focused on diseases (medicine and natural science) and does not acknowledge patients' resources and abilities to be experts in their own lives based on their lived experiences. Improving healthcare safety, quality,...
Patients' values and preferences for health states in allergic rhinitis-An artificial intelligence supported systematic review.
Allergy
Mar 29, 2024
BACKGROUND: Allergic rhinitis (AR) impacts patients' physical and emotional well-being. Assessing patients' values and preferences (V&P) related to AR is an essential part of patient-centered care and of the guideline development process. We aimed to...
Identification of Hit Compounds Using Artificial Intelligence for the Management of Allergic Diseases.
International journal of molecular sciences
Feb 14, 2024
This study aimed to identify and evaluate drug candidates targeting the kinase inhibitory region of suppressor of cytokine signaling (SOCS) 3 for the treatment of allergic rhinitis (AR). Utilizing an artificial intelligence (AI)-based new drug develo...
Association between household income levels and nutritional intake of allergic children under 6 years of age in Korea: 2019 Korea National Health and Nutrition Examination Survey and application of machine learning.
Frontiers in public health
Jan 8, 2024
INTRODUCTION: This study investigated the prevalence of allergic diseases in Korean children aged 6 and below, focusing on the interplay between nutritional status, household income levels, and allergic disease occurrence.
Specific IgE and IgG4 Profiles of House Dust Mite Components in Allergen-Specific Immunotherapy.
Frontiers in immunology
Feb 7, 2022
BACKGROUND: Allergen immunotherapy (AIT) can induce immune tolerance to allergens by activating multiple mechanisms, including promoting IgG4 synthesis and blunting IgE production. However, the longitudinal data of sIgE and sIgG4 to allergen componen...
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...
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