Device & Physiological Data
Supported data types can include ECG, EEG, PPG, SpO2, wearable-device outputs, remote-monitoring data and other device-generated healthcare information.
MEDICAL DEVICES & DIGITAL BIOMARKERS
Medical Devices
SCILabel supports medical-device and digital-health developers requiring representative healthcare datasets, signal annotation, clinical review and structured AI evaluation.
ECG
Signals, Devices & Monitoring
Physiological signal annotation and clinical review for connected devices and medical AI.
HOW WE SUPPORT YOUR TEAM
Specialist healthcare data operations
Build a workflow around your modality, use case, quality requirements and clinical expertise.
Annotation & Validation Workflows
Projects can include event labelling, signal classification, expert review, disagreement resolution and dataset-level quality checks.
AI Performance Evaluation
Evaluation programmes can assess defined performance criteria and clinically relevant error patterns using project-specific reference data.
CAPABILITIES
Configure the right workflow for your project
SCILabel combines healthcare data operations, trained taskers, specialist reviewers and project-level quality controls.
Discuss your requirements →
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ECG and cardiac signals
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EEG and neurological signals
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Wearables
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Remote monitoring
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Device-generated datasets
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Clinical review
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Model evaluation
SCILABEL WORKFLOW
From healthcare data to AI-ready delivery
1
SOURCE
2
PREPARE
3
ANNOTATE
4
REVIEW
5
QA
6
EVALUATE
7
VALIDATE
START A PROJECT
Build your next healthcare AI dataset with SCILabel
Tell us the data modality, use case, volume, geography, annotation requirements and timeline.