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Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell

In recent years, advancements in the field of artificial intelligence (AI) have impacted several areas of research and application. Besides more prominent examples like self-driving cars or media consumption algorithms, AI-based systems have further started to gain more and more popularity in the he...

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Autores principales: Milling, Manuel, Pokorny, Florian B., Bartl-Pokorny, Katrin D., Schuller, Björn W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9149088/
https://www.ncbi.nlm.nih.gov/pubmed/35651538
http://dx.doi.org/10.3389/fdgth.2022.886615
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author Milling, Manuel
Pokorny, Florian B.
Bartl-Pokorny, Katrin D.
Schuller, Björn W.
author_facet Milling, Manuel
Pokorny, Florian B.
Bartl-Pokorny, Katrin D.
Schuller, Björn W.
author_sort Milling, Manuel
collection PubMed
description In recent years, advancements in the field of artificial intelligence (AI) have impacted several areas of research and application. Besides more prominent examples like self-driving cars or media consumption algorithms, AI-based systems have further started to gain more and more popularity in the health care sector, however whilst being restrained by high requirements for accuracy, robustness, and explainability. Health-oriented AI research as a sub-field of digital health investigates a plethora of human-centered modalities. In this article, we address recent advances in the so far understudied but highly promising audio domain with a particular focus on speech data and present corresponding state-of-the-art technologies. Moreover, we give an excerpt of recent studies on the automatic audio-based detection of diseases ranging from acute and chronic respiratory diseases via psychiatric disorders to developmental disorders and neurodegenerative disorders. Our selection of presented literature shows that the recent success of deep learning methods in other fields of AI also more and more translates to the field of digital health, albeit expert-designed feature extractors and classical ML methodologies are still prominently used. Limiting factors, especially for speech-based disease detection systems, are related to the amount and diversity of available data, e. g., the number of patients and healthy controls as well as the underlying distribution of age, languages, and cultures. Finally, we contextualize and outline application scenarios of speech-based disease detection systems as supportive tools for health-care professionals under ethical consideration of privacy protection and faulty prediction.
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spelling pubmed-91490882022-05-31 Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell Milling, Manuel Pokorny, Florian B. Bartl-Pokorny, Katrin D. Schuller, Björn W. Front Digit Health Digital Health In recent years, advancements in the field of artificial intelligence (AI) have impacted several areas of research and application. Besides more prominent examples like self-driving cars or media consumption algorithms, AI-based systems have further started to gain more and more popularity in the health care sector, however whilst being restrained by high requirements for accuracy, robustness, and explainability. Health-oriented AI research as a sub-field of digital health investigates a plethora of human-centered modalities. In this article, we address recent advances in the so far understudied but highly promising audio domain with a particular focus on speech data and present corresponding state-of-the-art technologies. Moreover, we give an excerpt of recent studies on the automatic audio-based detection of diseases ranging from acute and chronic respiratory diseases via psychiatric disorders to developmental disorders and neurodegenerative disorders. Our selection of presented literature shows that the recent success of deep learning methods in other fields of AI also more and more translates to the field of digital health, albeit expert-designed feature extractors and classical ML methodologies are still prominently used. Limiting factors, especially for speech-based disease detection systems, are related to the amount and diversity of available data, e. g., the number of patients and healthy controls as well as the underlying distribution of age, languages, and cultures. Finally, we contextualize and outline application scenarios of speech-based disease detection systems as supportive tools for health-care professionals under ethical consideration of privacy protection and faulty prediction. Frontiers Media S.A. 2022-05-16 /pmc/articles/PMC9149088/ /pubmed/35651538 http://dx.doi.org/10.3389/fdgth.2022.886615 Text en Copyright © 2022 Milling, Pokorny, Bartl-Pokorny and Schuller. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Digital Health
Milling, Manuel
Pokorny, Florian B.
Bartl-Pokorny, Katrin D.
Schuller, Björn W.
Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell
title Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell
title_full Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell
title_fullStr Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell
title_full_unstemmed Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell
title_short Is Speech the New Blood? Recent Progress in AI-Based Disease Detection From Audio in a Nutshell
title_sort is speech the new blood? recent progress in ai-based disease detection from audio in a nutshell
topic Digital Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9149088/
https://www.ncbi.nlm.nih.gov/pubmed/35651538
http://dx.doi.org/10.3389/fdgth.2022.886615
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