SynthesisJournal of Alzheimer's disease : JAD2020
Artificial Intelligence, Speech, and Language Processing Approaches to Monitoring Alzheimer's Disease: A Systematic Review.
Synthesis in Journal of Alzheimer's disease : JAD, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07200739 (Development of Deep Learning Models for Detection of Neurodegenerative Diseases Using Speech - a Danish Language-based Artificial Intelligence Study), which is not on this map. Cited by 97 papers, 2 of them syntheses that pooled it.
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.
Development of Deep Learning Models for Detection of Neurodegenerative Diseases Using Speech - a Danish Language-based Artificial Intelligence Study (DetectAI)
Who cites it
97 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Machine Learning Approaches for Dementia Detection Through Speech and Gait Analysis: A Systematic Literature Review.Journal of Alzheimer's disease : JAD · 2024Pooled it
- Speech changes in old age: Methodological considerations for speech-based discrimination of healthy ageing and Alzheimer's disease.International journal of language & communication disordersPooled it
- Linguistic features from paragraph recall are markers of cognitive impairment.Journal of the International Neuropsychological Society : JINS · 2026Article
- Neural network-enhanced investigation of ferroptosis and druggability in early-onset alzheimer's disease.Metabolic brain disease · 2026Article
- PROTOCOL: Barriers and Facilitators to the Adoption of Speech-Based Cognitive Screening Tools: A Protocol for Systematic Review of Qualitative Evidence.Campbell systematic reviews · 2026Review
- The include network: Advancing cross-linguistic equity in brain health research.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Design of an artificial intelligence model to screen spontaneous speech to detect Alzheimer's Disease.PLOS digital health · 2026Article
- Speech-based digital cognitive assessment for clinical trials: Detecting cognitive impairment stages and AD biomarker relations across European cohorts.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Benchmarking speech biomarkers of Alzheimer's against cognitive and neural measures.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- Review of Artificial Intelligence for Clinical Use in Alzheimer's Disease and Related Dementias.Seminars in neurology · 2026Review
- Uncertainty modeling in multimodal speech analysis across the psychosis spectrum.NPJ digital medicine · 2026Article
- An End-to-End Overview of Clinical Speech AI.IEEE transactions on audio, speech, and language processing (2025) · 2026Article
- The Utility of Speech and Language Analytics for Screening Alzheimer's Disease.Neuro-degenerative diseases · 2026Review
- Acoustic Analysis of Primary Care Patient-provider Conversations to Screen for Cognitive Impairment.medRxiv : the preprint server for health sciences · 2025Article
- Evaluating spoken language as a biomarker for automated screening of cognitive impairment.Communications medicine · 2025Article
- A Hybrid Explainable AI Framework (HXAI) for Accurate and Interpretable Diagnosis of Alzheimer's Disease.Diagnostics (Basel, Switzerland) · 2025Article
- Article
- A systematic review of explainable artificial intelligence methods for speech-based cognitive decline detection.NPJ digital medicine · 2025Article
- Linguistic Markers in Spontaneous Speech: Insights into Subjective Cognitive Decline (Review).Healthcare (Basel, Switzerland) · 2025Review
- Automated Speech Markers of Alzheimer Dementia: Test of Cross-Linguistic Generalizability.Journal of medical Internet research · 2025Article
37 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
backgroundLanguage is a valuable source of clinical information in Alzheimer's disease, as it declines concurrently with neurodegeneration. Consequently, speech and language data have been extensively studied in connection with its diagnosis.
objectiveFirstly, to summarize the existing findings on the use of artificial intelligence, speech, and language processing to predict cognitive decline in the context of Alzheimer's disease. Secondly, to detail current research procedures, highlight their limitations, and suggest strategies to address them.
methodsSystematic review of original research between 2000 and 2019, registered in PROSPERO (reference CRD42018116606). An interdisciplinary search covered six databases on engineering (ACM and IEEE), psychology (PsycINFO), medicine (PubMed and Embase), and Web of Science. Bibliographies of relevant papers were screened until December 2019.
resultsFrom 3,654 search results, 51 articles were selected against the eligibility criteria. Four tables summarize their findings: study details (aim, population, interventions, comparisons, methods, and outcomes), data details (size, type, modalities, annotation, balance, availability, and language of study), methodology (pre-processing, feature generation, machine learning, evaluation, and results), and clinical applicability (research implications, clinical potential, risk of bias, and strengths/limitations).
conclusionPromising results are reported across nearly all 51 studies, but very few have been implemented in clinical research or practice. The main limitations of the field are poor standardization, limited comparability of results, and a degree of disconnect between study aims and clinical applications. Active attempts to close these gaps will support translation of future research into clinical practice.
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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.