HEAR4Health: a blueprint for making computer audition a staple of modern healthcare.

Autor:	Triantafyllopoulos A; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Kathan A; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Baird A; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Christ L; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Gebhard A; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Gerczuk M; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Karas V; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Hübner T; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Jing X; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Liu S; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Mallol-Ragolta A; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany.; Centre for Interdisciplinary Health Research, University of Augsburg, Augsburg, Germany., Milling M; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Ottl S; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Semertzidou A; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Rajamani ST; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Yan T; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Yang Z; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Dineley J; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Amiriparian S; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Bartl-Pokorny KD; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany.; Division of Phoniatrics, Medical University of Graz, Graz, Austria., Batliner A; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany., Pokorny FB; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany.; Division of Phoniatrics, Medical University of Graz, Graz, Austria.; Centre for Interdisciplinary Health Research, University of Augsburg, Augsburg, Germany., Schuller BW; EIHW - Chair of Embedded Intelligence for Healthcare and Wellbeing, University of Augsburg, Augsburg, Germany.; Centre for Interdisciplinary Health Research, University of Augsburg, Augsburg, Germany.; GLAM - Group on Language, Audio, & Music, Imperial College London, London, United Kingdom.
Jazyk:	angličtina
Zdroj:	Frontiers in digital health [Front Digit Health] 2023 Sep 12; Vol. 5, pp. 1196079. Date of Electronic Publication: 2023 Sep 12 (Print Publication: 2023).
DOI:	10.3389/fdgth.2023.1196079
Abstrakt:	Recent years have seen a rapid increase in digital medicine research in an attempt to transform traditional healthcare systems to their modern, intelligent, and versatile equivalents that are adequately equipped to tackle contemporary challenges. This has led to a wave of applications that utilise AI technologies; first and foremost in the fields of medical imaging, but also in the use of wearables and other intelligent sensors. In comparison, computer audition can be seen to be lagging behind, at least in terms of commercial interest. Yet, audition has long been a staple assistant for medical practitioners, with the stethoscope being the quintessential sign of doctors around the world. Transforming this traditional technology with the use of AI entails a set of unique challenges. We categorise the advances needed in four key pillars: Hear, corresponding to the cornerstone technologies needed to analyse auditory signals in real-life conditions; Earlier, for the advances needed in computational and data efficiency; Attentively, for accounting to individual differences and handling the longitudinal nature of medical data; and, finally, Responsibly, for ensuring compliance to the ethical standards accorded to the field of medicine. Thus, we provide an overview and perspective of HEAR4Health: the sketch of a modern, ubiquitous sensing system that can bring computer audition on par with other AI technologies in the strive for improved healthcare systems. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (© 2023 Triantafyllopoulos, Kathan, Baird, Christ, Gebhard, Gerczuk, Karas, Hübner, Jing, Liu, Mallol-Ragolta, Milling, Ottl, Semertzidou, Rajamani, Yan, Yang, Dineley, Amiriparian, Bartl-Pokorny, Batliner, Pokorny and Schuller.)
Databáze:	MEDLINE
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