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

2. november 2026 opdateret af: 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.

Studieoversigt

Status

Rekruttering

Betingelser

Intervention / Behandling

Detaljeret beskrivelse

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.

Undersøgelsestype

Interventionel

Tilmelding (Anslået)

200

Fase

  • Ikke anvendelig

Kontakter og lokationer

Dette afsnit indeholder kontaktoplysninger for dem, der udfører undersøgelsen, og oplysninger om, hvor denne undersøgelse udføres.

Studiekontakt

Undersøgelse Kontakt Backup

Studiesteder

Deltagelseskriterier

Forskere leder efter personer, der passer til en bestemt beskrivelse, kaldet berettigelseskriterier. Nogle eksempler på disse kriterier er en persons generelle helbredstilstand eller tidligere behandlinger.

Berettigelseskriterier

Aldre berettiget til at studere

40 år til 90 år (Voksen, Ældre voksen)

Tager imod sunde frivillige

Ja

Køn, der er berettiget til at studere

Alle

Beskrivelse

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.

Studieplan

Dette afsnit indeholder detaljer om studieplanen, herunder hvordan undersøgelsen er designet, og hvad undersøgelsen måler.

Hvordan er undersøgelsen tilrettelagt?

Design detaljer

  • Primært formål: Diagnostisk
  • Tildeling: Ikke-randomiseret
  • Interventionel model: Enkelt gruppeopgave
  • Maskning: Ingen (Åben etiket)

Våben og indgreb

Deltagergruppe / Arm
Intervention / Behandling
Aktiv komparator: Healthy Controls

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

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.

Eksperimentel: 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.

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.

Eksperimentel: frontotemporal dementia

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

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.

Eksperimentel: 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.

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.

Hvad måler undersøgelsen?

Primære resultatmål

Resultatmål
Foranstaltningsbeskrivelse
Tidsramme
Performance of AI-based language analysis in distinguishing diagnostic groups
Tidsramme: 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.)

Samarbejdspartnere og efterforskere

Det er her, du vil finde personer og organisationer, der er involveret i denne undersøgelse.

Sponsor

Samarbejdspartnere

Efterforskere

  • Ledende efterforsker: Petronilla Battista, PhD, Istituti Clinici Scientifici Maugeri IRCCS Bari
  • Studiestol: Gaia Santi, PhD, Istituti Clinici Scientifici Maugeri IRCCS Lumezzane
  • Studieleder: Simona Aresta, PhD, Istituti Clinici Scientifici Maugeri IRCCS Bari

Publikationer og nyttige links

Den person, der er ansvarlig for at indtaste oplysninger om undersøgelsen, leverer frivilligt disse publikationer. Disse kan handle om alt relateret til undersøgelsen.

Datoer for undersøgelser

Disse datoer sporer fremskridtene for indsendelser af undersøgelsesrekord og resumeresultater til ClinicalTrials.gov. Studieregistreringer og rapporterede resultater gennemgås af National Library of Medicine (NLM) for at sikre, at de opfylder specifikke kvalitetskontrolstandarder, før de offentliggøres på den offentlige hjemmeside.

Studer store datoer

Studiestart (Faktiske)

20. oktober 2025

Primær færdiggørelse (Anslået)

31. januar 2028

Studieafslutning (Anslået)

31. oktober 2028

Datoer for studieregistrering

Først indsendt

26. oktober 2026

Først indsendt, der opfyldte QC-kriterier

29. oktober 2026

Først opslået (Faktiske)

30. oktober 2026

Opdateringer af undersøgelsesjournaler

Sidste opdatering sendt (Faktiske)

3. november 2026

Sidste opdatering indsendt, der opfyldte kvalitetskontrolkriterier

2. november 2026

Sidst verificeret

1. oktober 2026

Mere information

Begreber relateret til denne undersøgelse

Andre undersøgelses-id-numre

  • Prot.2541/CEL

Plan for individuelle deltagerdata (IPD)

Planlægger du at dele individuelle deltagerdata (IPD)?

INGEN

IPD-planbeskrivelse

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.

Lægemiddel- og udstyrsoplysninger, undersøgelsesdokumenter

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