Stuttering is a widespread speech disorder affecting people globally, and it impacts effective communication and quality of life. Recent advancements in artificial intelligence (AI) and computational intelligence have introduced new possibilities for augmenting stuttering detection and treatment procedures. In this systematic review, the latest AI advancements and computational intelligence techniques in the context of stuttering are explored. By examining the existing literature, we investigated the application of AI in accurately determining and classifying stuttering manifestations. Furthermore, we explored how computational intelligence can contribute to developing innovative assessment tools and intervention strategies for persons who stutter (PWS). We reviewed and analyzed 14 refereed journal articles that were indexed on the from 2019 onward. The potential of AI and computational intelligence in revolutionizing stuttering assessment and treatment, which can enable personalized and effective approaches, is also highlighted in this review. By elucidating these advancements, we aim to encourage further research and development in this crucial area, enhancing in due course the lives of PWS.
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http://dx.doi.org/10.3390/diagnostics13233537 | DOI Listing |
Chaos
January 2025
Department of Computer Science and A.I. Andalusian Research Institute DaSCI "Data Science and Computational Intelligence, " University of Granada, 18071 Granada, Spain.
Reputation and punishment are significant guidelines for regulating individual behavior in human society, and those with a good reputation are more likely to be imitated by others. In addition, society imposes varying degrees of punishment for behaviors that harm the interests of groups with different reputations. However, conventional pairwise interaction rules and the punishment mechanism overlook this aspect.
View Article and Find Full Text PDFJAMA Netw Open
January 2025
National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, Maryland.
Importance: Digital health in biomedical research and its expanding list of potential clinical applications are rapidly evolving. A combination of new digital health technologies (DHTs), novel uses of existing DHTs through artificial intelligence- and machine learning-based algorithms, and improved integration and analysis of data from multiple sources has enabled broader use and delivery of these tools for research and health care purposes. The aim of this study was to assess the growth and overall trajectory of DHT funding through a National Institutes of Health (NIH)-wide grant portfolio analysis.
View Article and Find Full Text PDFJpn J Radiol
January 2025
Artificial Intelligence and Translational Imaging (ATI) Lab, Department of Radiology, School of Medicine, University of Crete, Voutes Campus, Heraklion, Greece.
Objective: Calcific tendinopathy, predominantly affecting rotator cuff tendons, leads to significant pain and tendon degeneration. Although US-guided percutaneous irrigation (US-PICT) is an effective treatment for this condition, prediction of patient' s response and long-term outcomes remains a challenge. This study introduces a novel radiomics-based model to forecast patient outcomes, addressing a gap in the current predictive methodologies.
View Article and Find Full Text PDFWorld J Pediatr
January 2025
Binjiang Institute of Zhejiang University, Hangzhou, 310053, China.
Background: Digital technologies play an important role in improving the quality of healthcare services, however, many healthcare workers and students do not recognize this and have low levels of digital competencies and skills. Therefore, this paper aims to investigate digital perceptions and competencies among medical students in pediatrics and pediatric healthcare workers in China.
Methods: A questionnaire on digital competency was designed.
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