Connectionists: CFP: Research Topic on Intelligent Audition Technologies for Personalized Healthcare - Deadline: 31 December

[Zhao Ren]

Dear colleagues,

we welcome your paper submissions to our Research Topic on INTELLIGENT  
AUDITION TECHNOLOGIES FOR PERSONALIZED HEALTHCARE.

https://www.frontiersin.org/research-topics/54868/intelligent-audition-technologies-for-personalized-healthcare

MANUSCRIPT SUBMISSION DEADLINE: 
31 December 2023

PARTICIPATING JOURNALS:

  Frontiers in Computer Science[1], Frontiers in Big Data[2],  
Frontiers in Artificial Intelligence[3], Frontiers in Digital Health[4]

    


TOPIC EDITORS:
Zhao Ren, University of Bremen, Germany
Tanja Schultz, University of Bremen, Germany
Kun Qian, Beijing Institute of Technology, China,
Björn W. Schuller, Technical University of Munich & Imperial College  
London, Germany & UK
 
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Over the past few decades, artificial intelligence has demonstrated  
its potential in helping with healthcare applications, including  
intelligent diagnosis, decision-making, and treatments using large  
amounts of medical data. Benefitting from signal processing, machine  
learning, and deep learning algorithms, computer audition is now  
rapidly emerging as an innovative instrument for effective, efficient,  
affordable, and non-invasive medical services using body acoustics and  
human speech. The new evolution of Internet-of-Things further  
increased the possibility of creating personalized healthcare with  
intelligent audition technologies, which can provide human-centered  
healthcare applications. The tendency toward developing machine  
learning and deep learning techniques in computer audition for  
personalized healthcare is promising and encouraging.

This Research Topic seeks to progress the interdisciplinary field of  
healthcare, artificial intelligence, and acoustic signal processing by  
facilitating the investigation of advanced methodologies and  
encouraging the development of new applications. The goal is to gather  
innovative works, including not only computer-audition prototypes for  
healthcare, but also cutting-edge machine-learning methodologies. This  
topic is finally expected to promote the development of trustworthy,  
dependable, sustainable artificial intelligence algorithms for  
personalized healthcare. This Research Topic is also thought of as a  
venue for audiences from the signal processing and computer science  
communities, as well as medical groups.

The Research Topic is looking for qualified research works in the  
field of intelligent audition technologies for personalized  
healthcare. Topics of interest include, but are not limited to:

- Prototypes of computer audition for healthcare applications
- New acoustic databases for study in healthcare
- Trustworthy machine learning approaches for computer audition in the  
healthcare sector
- Adversarial machine learning in computer audition for healthcare
- Dependable machine learning methods in computer audition for healthcare
- Methodologies and discussion in sustainability of machine learning  
for computer audition in the healthcare sector
***********************************************

Best regards,
Zhao Ren


Links:
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[1] https://www.frontiersin.org/journals/1511
[2] https://www.frontiersin.org/journals/1380
[3] https://www.frontiersin.org/journals/1437
[4] https://www.frontiersin.org/journals/1534
  Dr.-Ing. Zhao Ren
Cognitive Systems Lab (CSL)
University of Bremen
Germany
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