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

November 2, 2026 updated by: Istituti Clinici Scientifici Maugeri SpA

Analisi Automatizzata Del Linguaggio Nelle Malattie Neurodegenerative: Applicazione di Modelli di Intelligenza Artificiale

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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

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.

Study Type

Interventional

Enrollment (Estimated)

200

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

40 years to 90 years (Adult, Older Adult)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Description

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 informed consent.

Exclusion criteria

  • Mini-Mental State Examination (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.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Diagnostic
  • Allocation: Non-Randomized
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
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

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.
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

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.
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

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.
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

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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Performance of AI-based language analysis in distinguishing diagnostic groups
Time Frame: Day 1 (At completion of the one-time remote speech and language assessment and analysis.)

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

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Istituti Clinici Scientifici Maugeri SpA

Collaborators

IRCCS Policlinico S. Donato
Università degli studi di Trieste

Investigators

  • Principal Investigator: Petronilla Battista, PhD, Istituti Clinici Scientifici Maugeri IRCCS Bari
  • Study Chair: Gaia Santi, PhD, Istituti Clinici Scientifici Maugeri IRCCS Lumezzane
  • Study Director: Simona Aresta, PhD, Istituti Clinici Scientifici Maugeri IRCCS Bari

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

October 20, 2025

Primary Completion (Estimated)

January 31, 2028

Study Completion (Estimated)

October 31, 2028

Study Registration Dates

First Submitted

October 26, 2026

First Submitted That Met QC Criteria

October 29, 2026

First Posted (Actual)

October 30, 2026

Study Record Updates

Last Update Posted (Actual)

November 3, 2026

Last Update Submitted That Met QC Criteria

November 2, 2026

Last Verified

October 1, 2026

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • Prot.2541/CEL

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

IPD Plan Description

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.

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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