Predicting asthma attacks in New Zealand using machine learning - Vienna 2024

Artificial intelligence and machine learning in respiratory care: the features and algorithms for monitoring, diagnosis, prediction and advice

Chair(s): Vitalii Poberezhets, Cristina Isabel Oliveira J?come

Session type: Poster session

Predicting asthma attacks in New Zealand using machine learning

Widana Kankanamge Darsha Jayamini

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Objectives for algorithmic decision-making systems in childhood asthma: perspectives of children, parents, and physicians.

Omar Masrour

Poster

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AI-based diagnosis algorithm of pulmonary arterial hypertension using echocardiography

Jamol Uzokov

Poster

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Late Breaking Abstract - Increased adherence to Easyhaler DPI controller treatment with electronic sensor monitoring and mobile patient feedback in adult patients with asthma

Satu L?helm

Poster

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Late Breaking Abstract - The use of a digital inhalation coach reduces inhalation error rates in a clinical trial.

Laura Arendsen

Poster

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Late Breaking Abstract - Smart Talk for Allergies: Unveiling an AI Chatbot for Healthier Homes

Mingyu Kang

Poster

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Predicting exacerbation state of COPD patients with voice analysis: findings of the TACTICAS study

Loes Van Bemmel

Poster

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Reliability of real-world walking activity and gait assessment in people with COPD. How many hours and days are needed?

Joren Buekers

Poster

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Early detection of respiratory deterioration using continuous respiratory rate monitoring

Sherif Gonem

Poster

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Is tachycardia associated with post-COVID symptoms regardless of physical activity level?

Abstract

Longitudinal Cough Frequency Monitoring in Subjects with Persistent Cough: Daily Variability and Predictability Over 30 Days

Mindaugas Galvosas

Poster

Abstract

Predicting asthma attacks in New Zealand using machine learning

Widana Kankanamge Darsha Jayamini

Poster

Abstract

Machine learning implementation for enhanced respiratory sound classification: Assessing algorithmic efficacy

Patricia Alejandra Pe?a Torres

Poster

Abstract

Artificial Intelligence for Predicting Emergency Departments Visits in Kids with Asthma (AIRE-KIDS)

Dhenuka Radhakrishnan

Poster

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Artificial intelligence (AI) in detection of lung malignoma

Aleksandar Ivkovic

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Validation of a new, minimally-invasive, software smartphone device to predict sleep apnea and its severity

Juliette Millet

Poster

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Differentiating Cough Origins in Non-Contact AI Monitoring: Analyzing 'Non-User Coughs' with the Hyfe CoughMonitor Smartwatch

Mindaugas Galvosas

Poster

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Validation and Accuracy of the Automated AI-powered Continuous Hyfe Cough Monitoring System

Mindaugas Galvosas

Poster

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Late Breaking Abstract - Assessing the Clinical Benefit, Safety, and Patient-reported Outcomes with the Use of the PAHcare Digital Platform in Pulmonary Arterial Hypertension: A Pilot Study.

Carlos Ojeda Su?rez

Poster

Abstract

CDN Connection Issue

The ERS Congress 2024, Vienna

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