Artificial intelligence in assessment of neurogenic communication disorders in geriatric care: A literature review.
Purpose: With medical advancements contributing to increased life expectancy, the growing geriatric population has heightened the need for speech–language pathology services to address neurogenic communication impairments. Artificial intelligence (AI) offers promising opportunities to augment care a...
| Published in: | Journal of the All India Institute of Speech & Hearing Vol. 44; no. 2; pp. 102 - 110 |
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| Format: | review tables/charts Journal Article |
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Wolters Kluwer India Pvt Ltd
Jul-Dec2025
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| Online Access: | View this record in EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=191140367&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 191140367 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 0973662X B2H7 jtl: Journal of the All India Institute of Speech & Hearing issn: 0973662X maglogo: N pubinfo: dt: Jul-Dec2025 vid: 44 iid: 2 pid: 16919 pub: Wolters Kluwer India Pvt Ltd artinfo: ui: 191140367 191140367 191140367 10.4103/jaiish.jaiish_16_25 191140367 ppf: 102 ppct: 8 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Artificial intelligence in assessment of neurogenic communication disorders in geriatric care: A literature review. aug: au: Vora, Juhi affil: Winchester Medical Center sug: subj: Artificial Intelligence Utilization Communicative Disorders Diagnosis Neurologic Manifestations Diagnosis Gerontologic Care Dysarthria Diagnosis Aphasia Diagnosis Apraxia of Speech (Acquired) Diagnosis Automation Speech Therapy Voice Recognition Systems Natural Language Processing Machine Learning Deep Learning Decision Support Systems, Clinical Biological Markers Analysis Speech Physiology Language Tests Diagnosis, Computer Assisted Geriatric Assessment Assistive Technology ab: Purpose: With medical advancements contributing to increased life expectancy, the growing geriatric population has heightened the need for speech–language pathology services to address neurogenic communication impairments. Artificial intelligence (AI) offers promising opportunities to augment care and meet this rising demand. The purpose of this review was to synthesize current evidence on the use of AI in assessing neurogenic communication disorders in older adults. By focusing on clinical applications such as automatic speech recognition (ASR) and related AI tools, this review highlights their potential to improve efficiency, accessibility, and accuracy in assessment, while also addressing challenges to successful clinical integration. Materials and Methods: A literature review was performed using the keywords AI, ASR, aphasia, apraxia, and dysarthria on several databases, including PubMed, Google Scholar, and ASHA Journals Academy. Results: This review summarizes current attempts at incorporating AI in automating the detection and diagnosis of neurogenic communication disorders, including dysarthria, aphasia, and apraxia of speech. Conclusion: AI shows promise in the speech therapy field, in assisting with screening and evaluation of neurogenic communication disorders. However, clinical integration of these tools is challenging given their limitations with culturally and linguistically diverse datasets and concerns with ethical bias and data privacy. pubtype: Academic Journal doctype: review tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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