Asthma

Quality control, HPTLC analysis, antioxidant and antimicrobial activity of hydroalcoholic extract of roots of ( C.B Clarke).

OBJECTIVES: , CB Clarke () is a perennial herb of the Compositae family. The root of has been used for the treatment of various diseases such as hepatitis, jaundice, intestinal worms, bronchial asthma, and a variety of skin diseases. The aim of the study was to ensure quality control of and its preparation HAESL (hydroalcoholic extract of ) along with assessment of HAESL antimicrobial and antiox...

Pulmonary Ventilation Maps Generated with Free-breathing Proton MRI and a Deep Convolutional Neural Network.

Background Hyperpolarized noble gas MRI helps measure lung ventilation, but clinical translation remains limited. Free-breathing proton MRI may help quantify lung function using existing MRI systems without contrast material and may assist in providing information about ventilation not visible to the eye or easily extracted with segmentation methods. Purpose To explore the use of deep convolutiona...

Social robots and therapeutic adherence: A new challenge in pediatric asthma?

Social Robots are used in different contexts and, in healthcare, they are better known as Socially Assistive Robots. In the context of asthma, the use...

Parents' views on artificial intelligence for the daily management of childhood asthma: a survey.

Fusaroxazin, a novel cytotoxic and antimicrobial xanthone derivative from .

Oxazines and their derivatives are an uncommon natural heterocyclic compounds, which contain oxygen and nitrogen atoms and possess various bioactiviti...

Efficacy predictors of omalizumab in Chinese patients with moderate-to-severe allergic asthma: Findings from a analysis of a randomised phase III study.

BACKGROUND: Omalizumab has demonstrated efficacy as an add-on therapy in Chinese patients with moderate-to-severe allergic asthma. This analysis asse...

Early-Stage Feasibility of a Mobile Health Intervention (Copilot) to Enhance Exacerbation-Related Self-Management in Patients With Chronic Obstructive Pulmonary Disease: Multimethods Approach.

BACKGROUND: There is an emergence of mobile health (mHealth) interventions to support self-management in patients with chronic obstructive pulmonary d...

Machine learning prediction for mortality of patients diagnosed with COVID-19: a nationwide Korean cohort study.

The rapid spread of COVID-19 has resulted in the shortage of medical resources, which necessitates accurate prognosis prediction to triage patients ef...

Identification of exacerbation risk in patients with liver dysfunction using machine learning algorithms.

The prediction of the liver failure (LF) and its proper diagnosis would lead to a reduction in the complications of the disease and prevents the progr...

Successful Treatment of Allergic Bronchopulmonary Aspergillosis Using a Combination of Inhaled Fluticasone Furoate/Vilanterol and Oral Voriconazole.

Systemic corticosteroids are considered to be the standard treatment for allergic bronchopulmonary aspergillosis (ABPA). However, there is controversy...

A novel method based on infrared spectroscopic inception-resnet networks for the detection of the major fish allergen parvalbumin.

We have developed a novel approach that involves inception-resnet network (IRN) modeling based on infrared spectroscopy (IR) for rapid and specific de...

Artificial intelligence techniques in asthma: a systematic review and critical appraisal of the existing literature.

Artificial intelligence (AI) when coupled with large amounts of well characterised data can yield models that are expected to facilitate clinical prac...

Detecting asthma exacerbations using daily home monitoring and machine learning.

OBJECTIVE: Acute exacerbations contribute significantly to the morbidity of asthma. Recent studies have shown that early detection and treatment of as...

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

BACKGROUND: Asthma exacerbation is an acute or subacute episode of progressive worsening of asthma symptoms and can have a significant impact on patie...

Derivation of Breathing Metrics From a Photoplethysmogram at Rest: Machine Learning Methodology.

BACKGROUND: There has been a recent increased interest in monitoring health using wearable sensor technologies; however, few have focused on breathing...

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.

INTRODUCTION: Most asthma attacks and subsequent deaths are potentially preventable. We aim to develop a prognostic tool for identifying patients at h...

User-Centered Design of a Mobile Health Intervention to Enhance Exacerbation-Related Self-Management in Patients With Chronic Obstructive Pulmonary Disease (Copilot): Mixed Methods Study.

BACKGROUND: Adequate self-management skills are of great importance for patients with chronic obstructive pulmonary disease (COPD) to reduce the impac...

Experimental Data Based Machine Learning Classification Models with Predictive Ability to Select in Vitro Active Antiviral and Non-Toxic Essential Oils.

In the last decade essential oils have attracted scientists with a constant increase rate of more than 7% as witnessed by almost 5000 articles. Among ...

Pulmonary Embolism in Acute Asthma Exacerbation: Clinical Characteristics, Prediction Model and Hospital Outcomes.

PURPOSE: Little is known about the characteristics and impact of acute pulmonary embolism (PE) during episodes of asthma exacerbation. We aimed to cha...

Diagnosis of Asthma Based on Routine Blood Biomarkers Using Machine Learning.

Intelligent medical diagnosis has become common in the era of big data, although this technique has been applied to asthma only in limited contexts. U...