Asthma

AcousAF: Acoustic Sensing-Based Atrial Fibrillation Detection System for Mobile Phones

Atrial fibrillation (AF) is characterized by irregular electrical impulses originating in the atria, which can lead to severe complications and even death. Due to the intermittent nature of the AF, early and timely monitoring of AF is critical for patients to prevent further exacerbation of the condition. Although ambulatory ECG Holter monitors provide accurate monitoring, the high cost of these...

Accuracy of an Artificial Intelligence System for Interval Breast Cancer Detection at Screening Mammography.

Background Artificial intelligence (AI) systems can be used to identify interval breast cancers, although the localizations are not always accurate. Purpose To evaluate AI localizations of interval cancers (ICs) on screening mammograms by IC category and histopathologic characteristics. Materials and Methods A screening mammography data set (median patient age, 57 years [IQR, 52-64 years]) that ha...

UnPaSt: unsupervised patient stratification by differentially expressed biclusters in omics data

Most complex diseases, including cancer and non-malignant diseases like asthma, have distinct molecular subtypes that require distinct clinical appr...

Examining the effectiveness of artificial intelligence applications in asthma and COPD outpatient support in terms of patient health and public cost: SWOT analysis.

This research aimed to examine the effectiveness of artificial intelligence applications in asthma and chronic obstructive pulmonary disease (COPD) ou...

Towards Personalized Inhalation Therapy by Correlating Chest CT Imaging and Pulmonary Function Test Features Using Machine Learning.

Inhalation therapy is the predominant method of treatment for a variety of respiratory diseases. The effectiveness of such treatment is dependent on t...

SPIN: sex-specific and pathway-based interpretable neural network for sexual dimorphism analysis.

Sexual dimorphism in prevalence, severity and genetic susceptibility exists for most common diseases. However, most genetic and clinical outcome studi...

Ethical considerations for artificial intelligence in dermatology: a scoping review.

The field of dermatology is experiencing the rapid deployment of artificial intelligence (AI), from mobile applications (apps) for skin cancer detecti...

An intentional approach to managing bias in general purpose embedding models.

Advances in machine learning for health care have brought concerns about bias from the research community; specifically, the introduction, perpetuatio...

Deep Learning-based Time-to-event Analysis of Depression and Asthma using the All of Us Research Program.

While there is a growing recognition of the association between depression and asthma, few studies have leveraged deep learning-based (DL-based) model...

Machine learning approaches for asthma disease prediction among adults in Sri Lanka.

Addressing the challenge of cost-effective asthma diagnosis amidst diverse symptom patterns among patients, this study aims to develop a machine lear...

Artificial Intelligence and Family Medicine.

Artificial intelligence (AI) is certainly going to have a large, potentially huge, impact on the practice of family medicine. The specialty is fortuna...

Importance of GWAS Risk Loci and Clinical Data in Predicting Asthma Using Machine-learning Approaches.

INTRODUCTION: To understand the risk factors of asthma, we combined genome-wide association study (GWAS) risk loci and clinical data in predicting ast...

A framework for language technologies in behavioral research and clinical applications: Ethical challenges, implications, and solutions.

Technological advances in the assessment and understanding of speech and language within the domains of automatic speech recognition, natural language...

[CLINICAL APPLICATION OF ARTIFICIAL INTELLIGENCE ON AUXILIARY DIAGNOSIS OF ADULT ASTHMA].

Sputum Neutrophil Gelatinase-Associated Lipocalin as a Biomarker in Asthma-COPD Overlap.

BACKGROUND: Asthma COPD overlap (ACO) is a consensus-based phenotype having characteristics of both COPD and asthma. Distinguishing ACO from other dis...

DeepAlgPro: an interpretable deep neural network model for predicting allergenic proteins.

Allergies have become an emerging public health problem worldwide. The most effective way to prevent allergies is to find the causative allergen at th...

Exacerbations of COPD.

COPD exacerbations are associated with significant morbidity, mortality, and increased health care expenditures. The recently published Global Initiat...

[Robot-assisted Extended Thymectomy via a Bilateral Approach for Patients with Myasthenia Gravis].

Extended thymectomy is a procedure to remove the thymus gland and surrounding adipose tissue, while the traditional approach via a median sternotomy, ...

Automated Gas Chromatography Peak Alignment: A Deep Learning Approach using Greedy Optimization and Simulation.

The clinical significance of volatile organic compounds (VOC) in detecting diseases has been established over the past decades. Gas chromatography (GC...

Handling Class Imbalance in Machine Learning-based Prediction Models: A Case Study in Asthma Management.

A data-driven prediction tool has the potential to provide early warning of an asthma attack and improve asthma management and outcomes. Most previous...