Development of an optimal machine learning model to detect features of wheezing in children - Milan 2023

Digital health innovations in respiratory healthcare

Chair(s): Konstantinos Kostikas, Yet Hong Khor

Session type: Poster session

Development of an optimal machine learning model to detect features of wheezing in children

Kyunghoon Kim

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QUALITY OF ANDROID APPS FOR COPD AND ASTHMA PATIENTS IN UKRAINE

Mariia Tsyben

Poster

Abstract

Ballistocardiographic pad for detection of heart rate in respiratory diseases.

Vratislav Sedlak

Poster

Abstract

Transforming Irish health care delivery through digital health technology with a global orientation through the perspective lens of the service user

Tara Byrne

Poster

Abstract

The use of digital web-based video training for correct inhalation technique during the COVID-19 pandemic

Maximilian Wollsching-strobel

Poster

Abstract

Literature-mining in research of Post-Acute Sequelae of Covid-19

Kristina Piontkovskaya

Poster

Abstract

A wearable system for personal air pollution exposure: a walk-about in Milan

Sara Bernasconi

Poster

Abstract

Access to health care is a human right: a focus group study in COPD patients regarding eHealth accessibility

Esther I. Metting

Poster

Abstract

Development of the iRECHARGE web application (app) for Pulmonary Rehabilitation (PR) in India using Design Thinking Process (DTP)

Shruti Sahasrabudhe

Poster

Abstract

HHT Virtual Imaging Case Conferences - A New Way Forward for Rare Disease Management

Dilini Vethanayagam

Poster

Abstract

Feasibility and Safety of Oxygen Saturation Telemonitoring in Covid-19: an observational study

Jacopo Simonetti

Poster

Abstract

APPS FOR COPD AND ASTHMA PATIENTS IN UKRAINE: ANALYSIS OF ANDROID MARKETPLACE

Mariia Tsyben

Poster

Abstract

Development of an optimal machine learning model to detect features of wheezing in children

Kyunghoon Kim

Poster

Abstract

Evolution of patient perception and use of home spirometry over time

Karen Parsons

Poster

Abstract

Prediction of static lung volumes through spirometric parameters - a machine learning approach

Marco Pereira

Poster

Abstract

Prospective observational study of physical activity measurement using ePRO for evaluating the severity and prognosis in patients with interstitial pneumonia.

Kentaro Ito

Poster

Abstract

Barriers to digital usage for patients with chronic respiratory diseases

Mark Burns

Abstract

A machine learning-driven approach to improve patient-centered care in pulmonary fibrosis

Jiwon Jung

Poster

Abstract

Causes of failed smoking cessation attempts among active smokers.

Fatiha Bounoua

Abstract

AirPredict - A mobile app for monitoring personal exposure to Particulate Matter and respiratory outcomes in asthma patients

Michele Atzeni

Poster

Abstract

Environmental impact of a CF virtual clinic

David Green

Poster

Abstract

CDN Connection Issue

The ERS International Congress 2023, Milan

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