AI service — AI Medical · Dermatology
Skin lesion analysis
Classify and triage skin lesions from clinical and dermoscopic photographs, with concept-level explanation and label-efficient transfer.
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.
Teledermatology produces a high volume of photographs and a long queue. These models return multi-disease classification and risk stratification, or an embedding a classifier of your own is trained on, which is the practical route when your labelled set is in the hundreds rather than the hundred-thousands.
Images arrive over your API or from a triage inbox and come back as scored classes, embeddings or segmentation. Concept annotation models add the attribute-level signal — asymmetry, border, pigment network — that makes a score reviewable rather than opaque.
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 skin lesion analysis 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
- Triage queues — Rank teledermatology referrals so likely-malignant cases are seen first.
- Non-specialist support — Improve assessment accuracy where a dermatologist is not in the loop.
- Dataset auditing — Use concept scores to find bias and label error in an existing image set.
More Dermatology services
- Retinal image analysisRetinal image analysis service →
- Ultrasound analysisUltrasound analysis service →