AIMC Topic: Rhinitis, Allergic

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Construction of an intelligent screening model for allergic rhinitis based on routine blood tests.

PloS one
The incidence of allergic rhinitis (AR) has been increasing annually, severely impacting patients' quality of life and increasing socioeconomic burdens. The limitations of current diagnostic methods have made the development of efficient, low-cost ea...

Factors associated with allergic diseases in Chinese children aged 6-14 years.

BMC public health
BACKGROUND AND OBJECTIVES: We aimed to identify and optimize contributing factors associated with allergic diseases by machine/deep learning algorithms among school-age children aged 6-14 years.

Artesunate alleviates chronic allergic rhinitis and asthma syndrome via the CCR3/NF-κB pathway: a comprehensive analysis.

International immunopharmacology
BACKGROUND: Chronic allergic rhinitis and asthma syndrome (CARAS) is a comorbid inflammatory condition affecting both upper and lower airways, with limited treatment options. Artesunate (ART), a derivative of artemisinin, has shown anti-inflammatory ...

Deep learning-based allergic rhinitis diagnosis using nasal endoscopy images.

Scientific reports
Allergic rhinitis typically has edematous and pale turbinates or erythematous and inflamed turbinates. While traditional approaches include using skin prick tests (SPT) to determine the presence of AR, It is often not related to actual symptoms, and ...

Prediction of outpatient visits for allergic rhinitis using an artificial intelligence LSTM model - a study in Eastern China.

BMC public health
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
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
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 ...

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
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
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...