ClinicalTrials.gov
public full text
Public Domain
Prediction of Amyloid and Mild Cognitive Impairment in Early Stage Alzheimer's Disease From Remote Speech Phenotyping
The S22 study investigates, in a cross-sectional study, the ability of algorithms that analyse acoustic and linguistic patterns of spoken language to predict the presence of amyloid positivity in early stage Alzheimer's disease, specifically in Mild Cognitive Impairment (MCI) and cognitively normal (CN) cohorts; and whether similar algorithms can predict cognitive functioning, in classifying MCI vs CN.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Predicting PANSS symptoms in schizophrenia spectrum disorders using speech only: an international, multi-centre, retrospective, computational study across multiple languages#424607
- Reduced on-line speech gesture integration during multimodal language processing in adults with moderate-severe traumatic brain injury: Evidence from eye-tracking.#196010
- A Streaming End-to-End Framework For Spoken Language Understanding#1075949
- Listening Ahead: Phonological Prediction in Down Syndrome#1065518
- Evaluation of [123I] AV83 and SPECT in Patients With Alzheimer Disease in Comparison to Healthy Controls#885166
Record · ID 874669
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive