AIMC Topic: Asthma
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Audio-based digital biomarkers in diagnosing and managing respiratory diseases: a systematic review and bibliometric analysis.
European respiratory review : an official journal of the European Respiratory Society
Apr 1, 2025
Advances in wearable sensors and artificial intelligence have greatly enhanced the potential of digitised audio biomarkers for disease diagnostics and monitoring. In respiratory care, evidence supporting their clinical use remains fragmented and inco...
PNL: a software to build polygenic risk scores using a super learner approach based on PairNet, a Convolutional Neural Network.
Bioinformatics (Oxford, England)
Feb 4, 2025
SUMMARY: Polygenic risk scores (PRSs) hold promise for early disease diagnosis and personalized treatment, but their overall discriminative power remains limited for many diseases in the general population. As a result, numerous novel PRS modeling te...
Enhancing Asthma Self-Management with Environmental Passive-Monitoring Data and Machine Learning-Based Predictions.
Studies in health technology and informatics
Aug 22, 2024
Monitoring enables timely action which is critical in avoiding asthma attacks. With the abundance of local weather and pollution data, when augmented with machine learning, it is becoming possible to replace traditional tedious active monitoring in c...
Examining the effectiveness of artificial intelligence applications in asthma and COPD outpatient support in terms of patient health and public cost: SWOT analysis.
Medicine
Jul 19, 2024
This research aimed to examine the effectiveness of artificial intelligence applications in asthma and chronic obstructive pulmonary disease (COPD) outpatient treatment support in terms of patient health and public costs. The data obtained in the res...
SPIN: sex-specific and pathway-based interpretable neural network for sexual dimorphism analysis.
Briefings in bioinformatics
May 23, 2024
Sexual dimorphism in prevalence, severity and genetic susceptibility exists for most common diseases. However, most genetic and clinical outcome studies are designed in sex-combined framework considering sex as a covariate. Few sex-specific studies h...
Deep Learning-based Time-to-event Analysis of Depression and Asthma using the All of Us Research Program.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 1, 2024
While there is a growing recognition of the association between depression and asthma, few studies have leveraged deep learning-based (DL-based) models in a retrospective cohort study with a large sample size. We analyzed the association between depr...
Machine learning approaches for asthma disease prediction among adults in Sri Lanka.
Health informatics journal
Jan 1, 2024
Addressing the challenge of cost-effective asthma diagnosis amidst diverse symptom patterns among patients, this study aims to develop a machine learning-based asthma prediction tool for self-detection of asthma. Data from 6,665 participants in the...
[CLINICAL APPLICATION OF ARTIFICIAL INTELLIGENCE ON AUXILIARY DIAGNOSIS OF ADULT ASTHMA].
Arerugi = [Allergy]
Jan 1, 2024
Importance of GWAS Risk Loci and Clinical Data in Predicting Asthma Using Machine-learning Approaches.
Combinatorial chemistry & high throughput screening
Jan 1, 2024
INTRODUCTION: To understand the risk factors of asthma, we combined genome-wide association study (GWAS) risk loci and clinical data in predicting asthma using machine-learning approaches.
Sputum Neutrophil Gelatinase-Associated Lipocalin as a Biomarker in Asthma-COPD Overlap.
The Journal of the Association of Physicians of India
Sep 1, 2023
BACKGROUND: Asthma COPD overlap (ACO) is a consensus-based phenotype having characteristics of both COPD and asthma. Distinguishing ACO from other diseases is even more important as it is related to low health-related quality of life, augmented exace...
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