AI service — AI Medical · Neurology
EEG interpretation and sleep staging
Score polysomnography into sleep stages and turn EEG into embeddings for abnormality detection, event classification and BCI work.
Send us your data volume, throughput and latency targets and any constraint we should design around. You get a proposed configuration, a benchmark on your own data, and a known cost per unit of work before you commit.
Sleep scoring is thirty-second decisions across a whole night, and the agreement between two human scorers is itself only about 0.76 kappa. Automated staging reaches that level, which makes it a practical replacement for first-pass scoring rather than an aid to it.
EEG foundation models cover the wider ground: abnormality detection, event classification and downstream tasks trained on your own labels. Recordings arrive as EDF or your own format and come back as a hypnogram or scored events, with the model version recorded.
Every output is clinical decision support, not a diagnosis: a qualified professional reviews and signs it. Where clinical use requires regulatory approval in your jurisdiction, that approval remains yours to hold — we provide the infrastructure, the model operations and the audit trail behind it.
What we size for
We build the eeg interpretation and sleep staging pipeline around the workload you actually have: data format, accuracy target, latency, throughput, concurrency, retention and scheduling. Start with a pilot, then scale production capacity without changing a line of your integration.
Common use cases
- First-pass sleep scoring — Stage a whole night automatically for a technologist to review and adjust.
- Abnormal EEG triage — Rank recordings so likely-abnormal studies reach a reader first.
- Event detection — Mark spindles, slow waves and artefact across a cohort consistently.
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