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

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

Laura Arendsen

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

Omar Masrour

Poster

Abstract

AI-based diagnosis algorithm of pulmonary arterial hypertension using echocardiography

Jamol Uzokov

Poster

Abstract

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

Abstract

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

Laura Arendsen

Poster

Abstract

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

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

Patricia Alejandra Pe?a Torres

Poster

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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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