ClinicalTrials.gg
RecruitingNCT07906769AILANUpdated Nov 3, 2026

Automated Language Analysis in Neurodegenerative Diseases: Application of Artificial Intelligence Models

An interventional study of Speech and language Test to support clinical diagnosis in Alzheimer's Disease (AD), Frontotemporal Dementia (FTD) and Parkinsons Disease (PD), sponsored by Istituti Clinici Scientifici Maugeri SpA. Recruiting at 1 site in Italy. Open to participants aged 40 Years to 90 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-11-03.

Sponsored by Istituti Clinici Scientifici Maugeri SpA · Not applicable, Interventional, and Diagnostic

From the registry’s dates

  • Registered 1 year after the study started (first participant enrolled Oct 2025, registered Oct 2026).
  • Started Oct 2025; still recruiting 1 year later.
Updated Oct 30, 2026Newly registeredGo to Updates ↓
Phase
Not applicable
Study type
Interventional
Enrollment
200
Allocation
Non-randomized
Ages
40 Years to 90 Years
Sex
All
01

Study summary

This multicenter study aims to characterize the language profiles of patients with various neurodegenerative diseases, including Alzheimer's disease (AD), Primary Progressive Aphasia (PPA), behavioral variant Frontotemporal Dementia (bvFTD), Dementia with Lewy Bodies (DLB), and Parkinson's disease (PD), using artificial intelligence (AI) models. By analyzing speech and language data collected during remote neuropsychological assessments, the researchers intend to identify objective linguistic biomarkers suitable for early and differential diagnosis, overcoming the limitations of traditional, invasive, and costly diagnostic tools. The project will develop and validate an AI-driven pipeline to provide scalable and individualized linguistic profiles, ultimately supporting personalized treatment strategies and improving clinical workflow efficiency in the Italian population.

Read the detailed description

Neurodegenerative disorders pose significant diagnostic challenges, particularly in differentiating conditions with overlapping clinical symptoms and neuroanatomy. Although language impairment is a hallmark symptom across several forms of dementia, existing diagnostic tools are often costly, time-consuming, and lack cultural sensitivity, particularly for the Italian language. Artificial Intelligence (AI) offers a promising, non-invasive approach to extracting objective acoustic, prosodic, and linguistic markers from speech data.

The primary objective of this study is to characterize the language profiles of patients diagnosed with AD, PPA, bvFTD, DLB, and PD compared to healthy controls (HC). Specific objectives include: 1) Identifying distinct linguistic and speech features that act as surrogate biomarkers for early and differential diagnosis; 2) Using machine learning to optimize classification algorithms; and 3) Implementing Explainable AI (XAI) to ensure the interpretability of diagnostic outputs, thereby facilitating clinical trust and adoption of AI-driven tools in the diagnostic process.

This is a prospective, experimental, multicenter study. A total of 168 participants (24 per group: AD, PPA, bvFTD, DLB, PD, and HC) will be enrolled. Participants will undergo a 1.5-hour remote neuropsychological and logopedic evaluation via a secure, HIPAA-compliant videoconferencing platform. The assessment includes spontaneous speech tasks (e.g., image descriptions) and standardized language and cognitive tests. Audio data will be recorded and processed using an AI pipeline, including automatic speech recognition for transcription and various Natural Language Processing (NLP) techniques-such as BERT, RoBERTa, and UmBERTo-to extract complex linguistic and semantic features.

Data analysis will involve training machine learning classifiers (e.g., Support Vector Machines, Random Forests) to distinguish between diagnostic groups, utilizing nested cross-validation to ensure robustness. XAI techniques, including SHAP (Shapley Additive Explanations) and LIME (Local Interpretable Model-agnostic Explanations), will be applied to enhance the transparency of the model's decisions, allowing clinicians to interpret the pathological language patterns driving the classification. The study aims to establish the first structured Italian corpus for the linguistic characterization of neurodegenerative disorders, providing a foundation for future cross-linguistic analysis.

02

Conditions studied

  • Alzheimer's Disease (AD)
  • Frontotemporal Dementia (FTD)
  • Parkinsons Disease (PD)
  • Lewy Body Dementia

Keywords

  • Neurodegenerative diseases
  • Automated Speech and language analysis
  • Artificial intelligence (machine learning)
03

In context

Alzheimer Disease

3,965 studies on the registry are indexed under Alzheimer Disease; 926 are open to participants now.

This study's planned enrollment of 200 is above the median of 70 across 3,019 interventional studies indexed under Alzheimer Disease.

Browse Alzheimer Disease studies →

Lead sponsor

Istituti Clinici Scientifici Maugeri SpA is the lead sponsor of 126 studies on the registry; 51 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
40 Years to 90 Years
Sexes eligible
All
Accepts healthy volunteers
Yes

Eligibility criteria

Participants with neurodegenerative diseases

Inclusion criteria

  • Diagnosis of mild cognitive impairment due to Alzheimer's disease (AD), primary progressive aphasia (PPA), behavioral variant frontotemporal dementia (bvFTD), dementia with Lewy bodies (DLB), or Parkinson's disease (PD).
  • Age 40-85 years.
  • Italian native speaker.
  • Able to provide .

Exclusion criteria

  • (MMSE) score below 15.
  • Other neurological or psychiatric diagnoses, including cerebrovascular disease documented by MRI or CT.
  • Severe, uncorrected hearing or visual impairment.
  • Clinical Dementia Rating (CDR) score above 1.

Healthy controls

Inclusion criteria

  • Italian native speaker.
  • Matched to the patient groups for age, sex, and education level.

Exclusion criteria

  • History of systemic, neurological, or psychiatric disease.
  • Substance abuse.
  • Family history of neurodegenerative disease.
  • MMSE score below 27/30.
Terms in these criteria, in plain language(2)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

MMSE and MoCA

Short tests of memory and thinking, each scored out of 30. Lower scores suggest more difficulty; criteria give a range, either to include people with memory problems or to leave them out.

05

Study design

Phase
Not applicable
Primary purpose
Diagnostic
Allocation
Non-randomized
Intervention model
Single group
Masking
None (open label)
Enrollment
200 participants (estimated)

Study arms

  • Active comparator
    Healthy Controls

    Healthy control participants will complete a one-time remote speech and language assessment. No therapeutic intervention will be administered.

    Behavioral: Speech and language Test to support clinical diagnosis

  • Experimental
    Lewy bodies or Parkinson's

    Participants with dementia with Lewy bodies or Parkinson's disease will complete a one-time remote speech and language assessment. No therapeutic intervention will be administered.

    Behavioral: Speech and language Test to support clinical diagnosis

  • Experimental
    frontotemporal dementia

    Participants with frontotemporal dementia will complete a one-time remote speech and language assessment. No therapeutic intervention will be administered.

    Behavioral: Speech and language Test to support clinical diagnosis

  • Experimental
    Alzheimer's Disease (AD)

    Participants with Alzheimer's disease will complete a one-time remote speech and language assessment. No therapeutic intervention will be administered.

    Behavioral: Speech and language Test to support clinical diagnosis

Interventions

  • BehavioralSpeech and language Test to support clinical diagnosis

    Participants will complete a one-time remote speech and language assessment. Speech and language samples will be collected and analyzed using artificial intelligence and machine-learning methods. No therapeutic intervention will be administered.

06

What researchers measure

Primary outcomes

  1. Performance of AI-based language analysis in distinguishing diagnostic groups

    Accuracy of machine-learning models in classifying participants into the study groups (Alzheimer's disease, primary progressive aphasia, behavioral variant frontotemporal dementia, dementia with Lewy bodies, Parkinson's disease, and healthy controls) based on speech and language features from the remote assessment.

    Time frame: Day 1 (At completion of the one-time remote speech and language assessment and analysis.)

07

Study locations

1 of 1 sites recruiting
08

References and documents

Publications

  • Battista P, Salvatore C, Berlingeri M, Cerasa A, Castiglioni I. Artificial intelligence and neuropsychological measures: The case of Alzheimer's disease. Neurosci Biobehav Rev. 2020 Jul;114:211-228. doi: 10.1016/j.neubiorev.2020.04.026. Epub 2020 May 11. PubMed 32437744 ↗
  • Palmirotta C, Aresta S, Battista P, Tagliente S, Lagravinese G, Mongelli D, Gelao C, Fiore P, Castiglioni I, Minafra B, Salvatore C. Unveiling the Diagnostic Potential of Linguistic Markers in Identifying Individuals with Parkinson's Disease through Artificial Intelligence: A Systematic Review. Brain Sci. 2024 Jan 28;14(2):137. doi: 10.3390/brainsci14020137. PubMed 38391712 ↗
  • Battista, P., Aresta, S., Santacesaria, P., Benzini, A., Palmirotta, C., Tagliente, S., ... & Benussi, A. (2025). Natural Language Processing differentiates between Italian individuals with Nonfluent/Agrammatic from Logopenic variants of PPA. Alzheimer's & Dementia, 21, e105208.
  • Aresta S, Battista P, Palmirotta C, Tagliente S, Lagravinese G, Santacesaria P, Benzini A, Mongelli D, Minafra B, Lunetta C, Garcia AM, Salvatore C. Digital phenotyping of Parkinson's disease via natural language processing. NPJ Parkinsons Dis. 2025 Jun 23;11(1):182. doi: 10.1038/s41531-025-01050-8. PubMed 40550806 ↗

Individual participant data

Plan to share: No — Individual participant data will not be shared because the speech and language recordings and related clinical information are sensitive and potentially identifiable. The study team will protect participant confidentiality and use the data only for the purposes described in the protocol.

09

Timeline

2 registry updates since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reachedSimilar studies: half by the dot; the band is the middle halfHalf of similar studies reached it by the dot; the band is the middle half, from a quarter to three quarters

Started Oct 2025 (actual). Primary completion is estimated for Jan 2028, 27 months after the start.

Of 882 non-industry interventional studies with no phase under Alzheimer Disease, half reached primary completion within 30 months of starting (the median), counting those still running; a quarter within 15 and three quarters within 51. This study's planned 27 months is close to that.

Counting every sponsor, half of 959 studies reached it within 29 months; a quarter within 15 and three quarters within 51.

How these figures are worked out, and which studies are left out of them.

Registered
Oct 26, 2026
First posted
Oct 30, 2026
StartActual
Oct 20, 2025
Primary completionEst.
Jan 31, 2028
CompletionEst.
Oct 31, 2028
Last update
Nov 3, 2026
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
Registered
First appeared on the registry. No changes since
Oct 30, 2026
Show all 2 updates
  1. Nov 3, 2026
    Minor edits only
    + 1 other change: criteria formatting
  2. Oct 30, 2026
    First appeared on the registry

From the registry record's own update history. This site started tracking changes on Sep 25, 2026; for anything earlier, see the record history on ClinicalTrials.gov ↗

10

Registry details

Key details

Study ID
NCT07906769
Collaborators
Università degli studi di Trieste, IRCCS Policlinico S. Donato
Responsible party
Sponsor
First posted
Oct 30, 2026
Start date
Oct 20, 2025
Primary completion
Jan 31, 2028 (estimated)
Completion
Oct 31, 2028 (estimated)
Last update
Nov 3, 2026

Study contacts

Petronilla Battista, PhD
Contact
petronilla.battista@icsmaugeri.it
+390807814331
Gaia C Santi, PhD
Contact
gaia.santi@icsmaugeri.it
Petronilla Battista, PhD
principal investigator · Istituti Clinici Scientifici Maugeri IRCCS Bari
Gaia Santi, PhD
study chair · Istituti Clinici Scientifici Maugeri IRCCS Lumezzane
Simona Aresta, PhD
study director · Istituti Clinici Scientifici Maugeri IRCCS Bari

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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