aceHuman-artificial intelligence collaboration for comanaging epilepsy in real time
One-third of the world's 70 million people with epilepsy have seizures uncontrolled by medication, and implantable devices are a promising treatment. These devices can detect impending seizures, missed medication and impaired cognition, but, like most medical devices, they cannot share this information with patients in real time. This is a missed opportunity for devices to learn from clinical events and teach patients how their behaviors affect their health. Here we present a device platform that converses with…
In a pseudoprospective simulation, patient feedback alone improved seizure detector precision without expert intervention, reducing false alarms in a prototype that converses with patients.
The validation covered only 13 patients undergoing inpatient video-EEG monitoring, and the precision improvement was shown in a pseudoprospective simulation rather than live outpatient use.
Evidence
- Peer-reviewedNature Medicine2026-10-13
How should this claim be treated?
Truvace Impact Record TRV-2026-1616, v1: “Human-artificial intelligence collaboration for comanaging epilepsy in real time.” Truvace, 2026-10-16. /record/TRV-2026-1616 (accessed at citation time). sha256 60446f06d2d04276…
Calibration history
Every change to this record since certification, in the open. None yet — the reading has held since it entered the record.
Certified into the record
How to verify without trusting this page
Fetch the canonical text of any version from /api/record/TRV-2026-1616 and hash it yourself — for example shasum -a 256 on the saved canonical field. The result must equal content_hash, and each version’s text ends with prev:followed by the prior version’s hash (version 1 chains to 64 zeros). If a single character of any version had been altered since certification, the chain would not reproduce.