ArticleSensors (Basel, Switzerland)2024
Artificial Intelligence in Audiology: A Scoping Review of Current Applications and Future Directions.
Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
31 citing papers in PubMed.
- Evaluating the Impact of Hearing Conditioning App on Clinician Task Load and Hearing Test Efficiency in Children.The journal of international advanced otology · 2025Trial
- Artificial intelligence and hearing health: a global evidence review of biases and equity implications for Africa.Global health action · 2026Review
- Audiologist-Guided Multimodal AI for Pure-Tone Audiometry and Tympanometry Interpretation and Reporting.Journal of medical systems · 2026Article
- Turing problems in otolaryngology: a scoping review of the principal challenges of artificial ıntelligence and large language models.European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Review
- An Explainable Machine Learning Framework for Predicting Hearing Aid Satisfaction: Integrating the HATASS Instrument and Clinical Insights.Bioengineering (Basel, Switzerland) · 2026Article
- Management of Sudden Sensorineural Hearing Loss among General Practitioners in the United Kingdom: A Cross-Sectional Survey Study.International archives of otorhinolaryngology · 2026Article
- A Pressure-Centered Mechanistic Framework for Precision Otology: The Neuro-Vascular-Mechanical-Inflammatory-Autonomic (NVMIA) Regulatory Architecture.Journal of personalized medicine · 2026Review
- Perspectives of audiologists in China on artificial intelligence in clinical practice and professional identity: a qualitative study.BMC medical education · 2026Article
- Emerging Speech-in-Noise Tools for the Assessment of Hearing Loss: A Scoping Review.Audiology research · 2026Review
- Machine learning-enhanced behavioural approach to detecting reactions to sound in infants and toddlers: proof-of-concept study.International journal of audiology · 2026Article
- Personalized Hearing Loss Care Using SNOMED CT-Aligned Ontology and Random Forest Machine Learning: A Hybrid Decision-Support Framework.Audiology research · 2026Article
- Intelligent Decision Support for Transcatheter Aortic Valve Replacement: Machine Learning Spans From Anatomical Assessment to Dynamic Risk Modeling.Reviews in cardiovascular medicine · 2026Review
- Artificial Intelligence and Machine Learning in Audiology and Hearing Disorders: A Scoping Review with Bibliometric and Thematic Mapping (1995-2025).Audiology research · 2026Review
- Can a large language model inform patients about auditory brainstem implants?European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery · 2026Article
- Hearing health professionals' attitudes and perceived skills toward artificial intelligence.BMC medical education · 2026Article
- Deep Learning in Otolaryngology: A Narrative Review.JAMA otolaryngology-- head & neck surgery · 2026Review
- Observational
- Implementation and Evaluation of a Newborn Hearing Screening Database in a Resource-Limited Setting: Advantages and Limitations.Children (Basel, Switzerland) · 2025Article
- Computer models and artificial intelligence increase the fidelity and efficiency of the in vitro models for hearing loss.Biomedical engineering online · 2025Review
- A new approach to the intelligent decision support system for individual hearing aid selection and acquisition.Future science OA · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The integration of artificial intelligence (AI) into medical disciplines is rapidly transforming healthcare delivery, with audiology being no exception. By synthesizing the existing literature, this review seeks to inform clinicians, researchers, and policymakers about the potential and challenges of integrating AI into audiological practice. The PubMed, Cochrane, and Google Scholar databases were searched for articles published in English from 1990 to 2024 with the following query: "(audiology) AND ("artificial intelligence" OR "machine learning" OR "deep learning")". The PRISMA extension for scoping reviews (PRISMA-ScR) was followed. The database research yielded 1359 results, and the selection process led to the inclusion of 104 manuscripts. The integration of AI in audiology has evolved significantly over the succeeding decades, with 87.5% of manuscripts published in the last 4 years. Most types of AI were consistently used for specific purposes, such as logistic regression and other statistical machine learning tools (e.g., support vector machine, multilayer perceptron, random forest, deep belief network, decision tree, k-nearest neighbor, or LASSO) for automated audiometry and clinical predictions; convolutional neural networks for radiological image analysis; and large language models for automatic generation of diagnostic reports. Despite the advances in AI technologies, different ethical and professional challenges are still present, underscoring the need for larger, more diverse data collection and bioethics studies in the field of audiology.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.