Asthma

Predicting the Fine Particle Fraction of Dry Powder Inhalers Using Artificial Neural Networks.

Dry powder inhalers are increasingly popular for delivering drugs to the lungs for the treatment of respiratory diseases, but are complex products with multivariate performance determinants. Heuristic product development guided by in vitro aerosol performance testing is a costly and time-consuming process. This study investigated the feasibility of using artificial neural networks (ANNs) to predic...

Energy Efficient Monitoring of Metered Dose Inhaler Usage.

Life-long chronic inflammatory diseases of the airways, such as asthma and Chronic Obstructive Pulmonary Disease, are very common worldwide, affecting people of all ages, race and gender. One of the most important aspects for the effective management of asthma is medication adherence which is defined as the extent to which patients follow their prescribed action plan and use their inhaler correctl...

MAG-DPA curbs inflammatory biomarkers and pharmacological reactivity in cytokine-triggered hyperresponsive airway models.

Bronchial inflammation contributes to a sustained elevation of airway hyperresponsiveness (AHR) in asthma. Conversely, omega-3 fatty acid derivatives ...

Differential association of plasma monocyte chemoattractant protein-1 with systemic inflammatory and airway remodeling biomarkers in type-2 diabetic patients with and without asthma.

BACKGROUND: Chronic inflammation is a hallmark of type-2 diabetes (T2D) and asthma. Monocyte chemoattractant protein (MCP)-1 or CCL-2 is a key regulat...

Machine learning approaches to personalize early prediction of asthma exacerbations.

Patient telemonitoring results in an aggregation of significant amounts of information about patient disease trajectory. However, the potential use of...

Lung sound classification using cepstral-based statistical features.

Lung sounds convey useful information related to pulmonary pathology. In this paper, short-term spectral characteristics of lung sounds are studied to...

Planning the City Logistics Terminal Location by Applying the Green p-Median Model and Type-2 Neurofuzzy Network.

The paper herein presents green p-median problem (GMP) which uses the adaptive type-2 neural network for the processing of environmental and sociologi...

Use of a Robotic Sampler (PIPER) for Evaluation of Particulate Matter Exposure and Eczema in Preschoolers.

While the association of eczema with asthma is well recognized, little research has focused on the potential role of inhalable exposures and eczema. W...

Outcome of Inhaler Withdrawal in Patients Receiving Triple Therapy for COPD.

BACKGROUND: The purpose of this study was to document outcomes following withdrawal of a single inhaler (step-down) in chronic obstructive pulmonary d...

Evaluation of the impact of Flos Daturae on rat hepatic cytochrome P450 enzymes by cocktail probe drugs.

Flos Daturae, known as "baimantuoluo" or "yangjinhua" in China, has been used for centuries in Traditional Chinese Medicine for the treatment of asthm...

Powerful Tests for Multi-Marker Association Analysis Using Ensemble Learning.

Multi-marker approaches have received a lot of attention recently in genome wide association studies and can enhance power to detect new associations ...

Neuro-fuzzy classification of asthma and chronic obstructive pulmonary disease.

BACKGROUND: This paper presents a system for classification of asthma and chronic obstructive pulmonary disease (COPD) based on fuzzy rules and the tr...

Synthesis of -Mannich bases of berberine linking piperazine moieties revealing anticancer and antioxidant effects.

A new Mannich base series of piperazine linked berberine analogues was furnished in this study to screen the antioxidant and anticancer potential of t...

An Experimentation Platform for On-Chip Integration of Analog Neural Networks: A Pathway to Trusted and Robust Analog/RF ICs.

We discuss the design of an experimentation platform intended for prototyping low-cost analog neural networks for on-chip integration with analog/RF c...

Time-Aware Tranformer-Based Prediction Model for AECOPD

The rapid symptom change of Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) makes it critical to have time-sensitive prediction m...

A Two-Stage Time-Aware Transformer for Short-Horizon AECOPD Risk Prediction

Acute exacerbation of chronic obstructive pulmonary disease (AECOPD) can worsen rapidly, making timely prediction a clinical priority. Most existing m...

Explainable Transformer Models for Clinical Prediction Tasks on Structured Electronic Health Records

Predictive models over structured electronic health records (EHRs) remain central to machine learning for healthcare, but few have jointly emphasized ...

Generative AI Use for Mental Health Support: Patterns, Correlates, and Impact among Canadian Students

Background. General purpose generative AI (GenAI) chatbots are increasingly used by students for mental health support. Research on prevalence estimat...

Genetic decoding reveals druggable biology implicitly learned by a medical-history foundation model

Foundation models trained on electronic healthcare records (EHRs) have gained traction with the aim to transform personalised medicine. However, their...

Patient-Level Risk Characterization of Drug-Associated Hidradenitis Suppurativa Using Machine Learning

Hidradenitis suppurativa (HS) is a chronic, debilitating, inflammatory skin disorder. Medications have been reported in association with cases of new-...