Learn · Source-linked curriculum

Surgical AI, taught from the operating-room question outward.

Five structured tracks connect technical concepts to clinical context, evidence quality, failure modes, and responsible translation. Every public lesson passes human editorial review.

Five tracks · 30 lessons

Build a shared vocabulary across surgery, research, and engineering.

Lessons include learning objectives, applied exercises, knowledge checks, limitations, and links to primary research or reporting guidance.

TRACK 016 published

Foundations of Surgical Data Science

Define the field, map operating-room data, and distinguish observations, labels, predictions, and clinical interventions.

Foundation6 lessons60–90 min

TRACK 026 published

Surgical Video AI

Learn how time, visibility, workflow, anatomy, and intended use change computer-vision research in surgery.

Foundation6 lessons60–90 min

TRACK 036 published

Datasets and Annotation

Design defensible labels, measure disagreement, avoid leakage, and judge whether a dataset fits its question.

Intermediate6 lessons60–90 min

TRACK 046 published

Models and Evaluation

Interpret metrics, shortcuts, validation, explainability, benchmarks, and foundation-model claims.

Intermediate6 lessons60–90 min

TRACK 056 published

Translation and Clinical Integration

Move from research prototype to bounded clinical use through workflow, safety, governance, and evidence.

Advanced6 lessons60–90 min

The Weekly Signal

Keep learning as the evidence changes.

A concise email with practical explainers, useful papers, dataset updates, tools, and ways to participate.

Read and subscribe