Research project A3S: AI-based Asthma App using Spirometer
The A3S project aims to create an AI-powered asthma app with a spirometer, using explainable AI to analyze patient data and guide decisions. It focuses on transparent, person-centered care to help people manage asthma and reduce health risks.
Asthma is a common but serious condition that affects millions worldwide. To help patients manage their health, the Swedish company MediTuner AB developed AsthmaTuner, a digital tool combining a handheld spirometer with a mobile app.
This research project plans to take the tool a step further by adding explainable AI (XAI) to create the A3S system (AI-based Asthma App using Spirometer).
Unlike traditional “black-box” AI, XAI provides clear, understandable explanations for its decisions. In A3S, XAI will analyze patient data and guide asthma care, helping both users and healthcare professionals make better-informed choices. A key goal is to offer personalized support that considers social factors affecting asthma patients, particularly those in disadvantaged groups.
By improving diagnosis and management, A3S aims to reduce unnecessary hospital visits, prevent severe asthma attacks, and promote better respiratory health. This cutting-edge approach could transform asthma care worldwide.
Project description
Explainable Artificial Intelligence (XAI) has a high potential to enhance existing digital tools previously developed without AI or with black-box AI. AsthmaTuner, an existing remote digital tool owned by MediTuner AB in Sweden, consists of a handheld spirometer connected to a mobile app that can be used by patients with asthma and other respiratory diseases to diagnose and manage their health conditions. The existing AsthmaTuner system does not use any AI so far, and naturally, the scope of using black-box AI has a high potential.
Objective
In this project, we pursue a significant step ahead. We will explore how XAI will enhance both the diagnostic and management capabilities of the AsthmaTuner system. That means XAI will help both patient users and their health care providers further improve asthma care, with the target of reduced need for unnecessary health care visits or costly and potentially deadly asthma attacks or exacerbations. The XAI-based digital tools are expected to prevent further health disparities and will include the addition of social determinants of health to the design, implementation, and evaluation of AsthmaTuner to improve its performance.
Background
Asthma is a large-scale health care problem, affecting around 10 percent of the European population. Moreover, asthma and other respiratory diseases are increasing due to environmental deterioration worldwide. Asthma is a complex problem, which is characterized by airway inflammation and respiratory symptoms of wheezing, dyspnea, chest tightness and cough that vary over time and in intensity, together with variable expiratory airflow limitation.
Potentially effective ways to address asthma care are to better understand the day-to-day lung function (a longitudinal data) and asthmatic symptoms of individuals and more effectively identify, diagnose, and manage asthma by exploring potential disparities in symptoms, lung function, and outcomes that may exist by social determinants for patients. AsthmaTuner (AT) is the existing, validated digital tool in this regard.
The general purpose of the project is to design an explainable AI (XAI)-based smart AT system that uses a mobile app and a handheld spirometer. We refer to it as “A3S: AI-based Asthma App using Spirometer”. For the A3S system development, XAI algorithms will perform patient data analysis and guide decisions. The term “explainable” in XAI refers to the ability of these algorithms to provide transparent and interpretable explanations to patients and health care professionals for their predictions or decisions.
The XAI algorithms will provide person-centred interventions precluding the onset or minimizing the risk of asthma in disadvantaged groups. It will help to improve respiratory health by training person-centred AI-support in asthma diagnosis and management of asthma in disadvantaged groups based on social determinants. Overall, the A3S project addresses a pressing health care problem with potentially widespread impact.
Project members
Project managers
Ioanna Miliou
Senior Lecturer
