Alzheimer's Disease
Alzheimer's Disease screening by GIA®, powered by digitalhumanOS™, uses Voice AI, Computer Vision, and Speech Biomarkers to detect alzheimer's disease through a single patient conversation. Screening performance: Clinically validated vocal biomarker screening. Screening takes under 5 minutes with results in 60 seconds.
Early Alzheimer's detection allows for supportive care, maximizing patient comfort and dignity.
Alzheimer's screening enables proactive care planning in post-acute settings. By identifying the disease early, we can provide supportive care and improve quality of life.
Key Facts
- Screening Time
- Under 5 minutes
- Results
- 60 seconds
- Modalities
- Voice + Vision + Speech
- Registration
- 510(k)
- Status
- Live
About Alzheimer's Disease screening.
How does this screening work?
The AI analyzes speech patterns, vocal characteristics, and cognitive tasks to assess cognitive function.
What is the benefit of early detection?
Early detection allows for access to available treatments, participation in clinical trials, and advanced care planning.
Has this Alzheimer's Disease screener been validated clinically?
Yes, this system has been clinically validated to assist in early Alzheimer's detection.
The science behind Alzheimer's Disease screening.
With an estimated 46.7 million Americans aged 65 and older living with Alzheimer's or related dementia, peer-reviewed research validates vocal biomarker models for early Alzheimer's detection — identifying cases before clinical symptoms become apparent.
Alzheimer's Model Performance (2022-05)Research demonstrates that Alzheimer's disease indicators are detectable through vocal biomarker analysis in conversational settings — including telephone interactions — making screening possible in any patient encounter.
Detecting Alzheimer's Disease in a Call Center Using Vocal Biomarkers (2018-06)The Framingham Heart Study, analyzing over 4,000 voice recordings paired with MRI-derived brain data, found that vocal markers including jitter, articulation rate, and lexical diversity are significantly associated with structural changes in memory-related brain regions.
Framingham Heart Study — Voice and Brain Structure Correlation (2026-03) · NIH Bridge2AI-Voice Consortium, Boston University, Vanderbilt University Medical Center