The result to aim for
For prostate cancer, Dr. Guillaume Herpe uses an algorithm that identifies at-risk lesions on MRI, produces segmentation, volume, classification and risk prediction: "All this is done automatically. But the radiologist can control the position. »
What was done
France 3 Nouvelle-Aquitaine (Elsa Versapuy, 22 July 2026), same article. The transition zone, he says, "must be analyzed automatically, because we don't have time to do […] segmentation." Tobacco screening / pulmonary nodules: announced, untitled. Distinct from the synthetic sheet and fractures.
Before you start
Tool cited by the source: algorithme IRM prostate; other tools cited: algorithme d’imagerie. Fill in the bracketed items: [volume, classification, localisation], [coller 6 lignes]. Strip confidential data that is not needed and check your tool’s access terms. Features and plans can change.
The method, in three steps.
Gather the context
Spot the bracketed items in the prompt (
[volume, classification, localisation],[coller 6 lignes]) and prepare what they ask for.Adapt the prompt
Copy the prompt below, replace the bracketed items, then paste it into the AI assistant you use. The cited tool (algorithme IRM prostate) is not necessarily available to the public..
Reread before using
Reread the result, correct it if needed and keep the final decision. Caveats are detailed below.
Your starting point.
Replace the bracketed items, then adapt the proposal to your situation. This prompt is written by the iadujour desk It is not a quotation from the source.
Tool proposal (facts): [volume, classification, localisation]. What I saw: [coller 6 lignes]. Table: lesion, what the tool says, what I have to control. Don't make up any scores.
What deserves your attention
Proof level: Testimony published by an identified source. Source checked on 11 November 2026. Use described by the source, not tested by the desk. Original summary written by iadujour.fr: figures and claims are the source’s; the prompt is a desk proposal, not a quotation.
Comments.
A field note, a question, a precision on this use case? Comments are reviewed before publication.
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