Clinical judgment
Labels and references reflect diagnostic reasoning, treatment logic, and clinical risk — not surface-level text patterns.
Linco provides medical data annotation performed by qualified physicians — clinical labels, reference answers, rubrics, and evaluation datasets created by people who understand medicine, not just labeling tools.
In medicine, an incorrect label is not a cosmetic issue — it teaches the model the wrong clinical signal. Annotating symptom severity, treatment appropriateness, diagnostic reasoning, or patient safety risk requires clinical judgment, familiarity with medical evidence, and awareness of how care is actually delivered. That is why every Linco annotation project is staffed with qualified physicians.
Labels and references reflect diagnostic reasoning, treatment logic, and clinical risk — not surface-level text patterns.
Shared rubrics, structured guidance, and coordinated physician cohorts keep annotations consistent across large datasets.
Annotation can reflect Ethiopian and East African clinical contexts, disease patterns, and healthcare settings where relevant to your data.
Annotation work is defined project by project. Common outputs include:
Physician-applied labels on clinical text, dialogue, imaging reports, and medical records-style data — grounded in real clinical understanding rather than general labeling.
Expert-written model answers that define what a correct, complete, and clinically safe response looks like for a given prompt or case.
Evaluation rubrics and grading criteria authored by clinicians, so automated and human scoring measure what actually matters medically.
Structured datasets for benchmarking and regression testing of medical-AI systems, built to project-specific clinical requirements.
Flags for unsafe, misleading, incomplete, or clinically inappropriate content, applied by people trained to recognize clinical risk.
Annotation and expert review involving English and Ethiopian languages, including Amharic, with coverage expanding as the network grows.
Physician-annotated data supports medical-AI teams across training, evaluation, and safety work. Requirements, specialty mix, and language coverage are defined per project.
Annotation projects are delivered through Linco's Ethiopia-first physician network. Experts pass a structured qualification process covering professional credentials, clinical expertise, safety judgment, and project readiness before participating in work. Linco coordinates the cohort, the workflow, and delivery — your team works with one relationship, not individual contractors.
Credential-verified physicians, structured through the Linco Expert Readiness Framework.
Specialty, language, and capacity matched to your dataset and guidelines.
Linco coordinates workflows and delivery so your team focuses on the model.
Learn more about how experts are qualified and the broader medical-AI expertise Linco provides.
Share the data type, annotation guidelines, specialty mix, language requirements, and volume.
Linco assesses current expert availability and confirms whether the requirement can be supported.
A managed physician cohort produces the annotation work to your specification and timeline.
For the full range of expert services, see Solutions.
Tell us about your dataset, guidelines, specialty and language requirements, and the capacity you are looking for.