Evidence map›Paper›PMID 35049736›Full record

ReviewBioengineering (Basel, Switzerland)2022

Speech- and Language-Based Classification of Alzheimer's Disease: A Systematic Review.

Inês Vigo, Luis Coelho, Sara Reis

Abstract readReview
In one paragraph

Review in Bioengineering (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Language dysfunction as a primary feature of cognitive decline in neurological populations.Journal of neural transmission (Vienna, Austria : 1996) · 2026
    Review
  5. Article
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  8. The association of common infectious exposures with cognitive performance in community-dwelling older adults.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2025
    Article
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  11. Adversarial Text Generation using Large Language Models for Dementia Detection.Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing · 2024
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Inês VigoInstituto Superior de Engenharia do Porto, 4249-015 Porto, Portugal.
Luis CoelhoInstituto Superior de Engenharia do Porto, 4249-015 Porto, Portugal.
Sara ReisInstituto Superior de Engenharia do Porto, 4249-015 Porto, Portugal.

Funding

Fundação para a Ciência e Tecnologia FCT- UIDB/04730/2020
6 · The paper itself

Abstract

backgroundAlzheimer's disease (AD) has paramount importance due to its rising prevalence, the impact on the patient and society, and the related healthcare costs. However, current diagnostic techniques are not designed for frequent mass screening, delaying therapeutic intervention and worsening prognoses. To be able to detect AD at an early stage, ideally at a pre-clinical stage, speech analysis emerges as a simple low-cost non-invasive procedure.

objectivesIn this work it is our objective to do a systematic review about speech-based detection and classification of Alzheimer's Disease with the purpose of identifying the most effective algorithms and best practices.

methodsA systematic literature search was performed from Jan 2015 up to May 2020 using ScienceDirect, PubMed and DBLP. Articles were screened by title, abstract and full text as needed. A manual complementary search among the references of the included papers was also performed. Inclusion criteria and search strategies were defined a priori.

resultsWe were able: to identify the main resources that can support the development of decision support systems for AD, to list speech features that are correlated with the linguistic and acoustic footprint of the disease, to recognize the data models that can provide robust results and to observe the performance indicators that were reported. DISCUSSION: A computational system with the adequate elements combination, based on the identified best-practices, can point to a whole new diagnostic approach, leading to better insights about AD symptoms and its disease patterns, creating conditions to promote a longer life span as well as an improvement in patient quality of life. The clinically relevant results that were identified can be used to establish a reference system and help to define research guidelines for future developments.

Indexed as

Alzheimer’s disease (AD)classificationfeaturesmachine learning (ML)mild cognitive impairment (MCI)speech

Identifiers

PMID35049736
PMCPMC8772820

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.