We found a match
Your institution may have access to this item. Find your institution then sign in to continue.
- Title
Voice as a Biomarker of Pediatric Health: A Scoping Review.
- Authors
Rogers, Hannah Paige; Hseu, Anne; Kim, Jung; Silberholz, Elizabeth; Jo, Stacy; Dorste, Anna; Jenkins, Kathy
- Abstract
The human voice has the potential to serve as a valuable biomarker for the early detection, diagnosis, and monitoring of pediatric conditions. This scoping review synthesizes the current knowledge on the application of artificial intelligence (AI) in analyzing pediatric voice as a biomarker for health. The included studies featured voice recordings from pediatric populations aged 0–17 years, utilized feature extraction methods, and analyzed pathological biomarkers using AI models. Data from 62 studies were extracted, encompassing study and participant characteristics, recording sources, feature extraction methods, and AI models. Data from 39 models across 35 studies were evaluated for accuracy, sensitivity, and specificity. The review showed a global representation of pediatric voice studies, with a focus on developmental, respiratory, speech, and language conditions. The most frequently studied conditions were autism spectrum disorder, intellectual disabilities, asphyxia, and asthma. Mel-Frequency Cepstral Coefficients were the most utilized feature extraction method, while Support Vector Machines were the predominant AI model. The analysis of pediatric voice using AI demonstrates promise as a non-invasive, cost-effective biomarker for a broad spectrum of pediatric conditions. Further research is necessary to standardize the feature extraction methods and AI models utilized for the evaluation of pediatric voice as a biomarker for health. Standardization has significant potential to enhance the accuracy and applicability of these tools in clinical settings across a variety of conditions and voice recording types. Further development of this field has enormous potential for the creation of innovative diagnostic tools and interventions for pediatric populations globally.
- Subjects
LUNG disease diagnosis; DIAGNOSIS of autism; ASTHMA diagnosis; SPEECH disorder diagnosis; DIAGNOSIS of child development deviations; LANGUAGE disorder diagnosis; PREDICTIVE tests; MEDICAL information storage &; retrieval systems; HEALTH status indicators; RESEARCH funding; ARTIFICIAL intelligence; RESEARCH evaluation; ASPHYXIA; SYSTEMATIC reviews; INTELLECTUAL disabilities; LITERATURE reviews; MEDICAL databases; HUMAN voice; BIOMARKERS; SENSITIVITY &; specificity (Statistics); CHILDREN
- Publication
Children, 2024, Vol 11, Issue 6, p684
- ISSN
2227-9067
- Publication type
Article
- DOI
10.3390/children11060684