A shared decision-making app for liver surgery. With Toys Films, under the medical supervision of Dr Oriana Ciacio and Prof. Éric Vibert.
BOPA 2 · 2025-2030
Augmenting the patient journey
Improving the quality and safety of care at every stage of surgery: before, during and after the operation.
Watch
Innovations in action
Before surgery
Communicate better with the patient
A patient who understands the proposed treatment strategy adheres better to their care pathway. Given the complexity of the procedures, diagrams are essential.
The equivalent app for pancreatic surgery, under the medical supervision of Dr Gabriella Pittau.
Measuring their impact on the treatment strategy and building a pre-operative storyboard.
During surgery
Analyse the real, assist the gesture
The OR is not an aircraft cockpit and surgeons are not pilots: the "black box" is not socially acceptable — a conclusion grounded in sociological research carried out within BOPA (Nicolas El Haïk-Wagner's doctoral thesis). BOPA moves from the black box to intra-operative assistance through data science.
A "made in BOPA" device: a headset that films the surgeon's hands during open surgery. Live image analysis, augmented reporting, tele-expertise, a surgical video library.
A semi-automatic report with images and diagrams, and real-time coding, from video analysis of the surgery (from LLM to Vision Large Model).
An AI agent to ask the surgeon questions during the operation. "From AI that sees to AI that understands." Targeted for completion before 2028.
A reliable, complete source of information about the patient — checklist, history. Demonstration planned for 2027.
These agents run on Small Language Models, more frugal and better controlled than large generic models. Also under exploration: neurosciences (surgeon's focus), light analysis, tele-expertise and cobotics.
After surgery
Follow up and evaluate better
A chatbot to support liver-transplant patients around the clock. Development complete, clinical study under way; a vision of national deployment.
Assessing the patient's quality of life and experience (AP-HP's Value-Based Health Care axis), via the SKEZIA platform.
Using health data (PMSI) with double machine learning and causal inference to understand outcome variations and reduce complications.
Content established from the chair's presentation (2026). Some collaborator names and clinical figures remain to be confirmed before final publication.