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Description

Deep learning and data science are evolving rapidly, making applications that would have been unthinkable until a few years ago possible, even in the medical-surgical domain. At the same time, surgery is starting to introduce robotic instruments that claim “intelligent” functions. As these robotic devices become more complex and autonomous, greater intelligence and knowledge are required of them. Thus, a pressing challenge is how to give them such knowledge in a transparent and balanced way that meets all the ethical requirements and that could be automatically extracted from the available information or from the data collected during the intervention.

In the robotic-surgical world, these data are multimodal and include videos of interventions, pre- or intraoperative images, alarms, dialogues between clinicians in the operating room, written notes and surgical textbooks, or kinematic data collected by the robot sensors. Despite the growing interest in data-driven approaches in surgical robotics, there are no success stories yet in translating these findings to practical robotic surgery applications because of the small community addressing this area and the lack of communication with other stakeholders.

This workshop wants to investigate the possible applications that surgical data science can have in robotic surgery, paying particular attention to the extraction of surgical workflows from multimodal data collected before or during surgery and the verification of certifiability of the models obtained. Furthermore, this workshop wants to contribute to the growth and impact of surgical data science in surgical robotics, analyze current gaps in the successful practical implementation of data-driven approaches in robotic surgery, and propose concrete steps to strengthen the field.

To encourage the exchange of ideas, we will organise brainstorming sessions where participants will be asked for opinions about the workshop topics. The answers will be collected and discussed during a final round table.

Call for Papers

We invite submissions to this workshop to investigate the possible applications that surgical data science can have in robotic surgery. Furthermore, this workshop wants to contribute to the growth and impact of surgical data science in surgical robotics, analyze current gaps in the successful practical implementation of data-driven approaches in robotic surgery, and propose concrete steps to strengthen the field.

Authors of the accepted papers will be invited to present their work as poster in dedicated sessions. Further details on the call can be found here.

Deadline extended to 20th May!

Programme

08:30 - 09:00	Registration & Coffee
09.00 - 09.05	Presentation from the organizers
09.05 - 09.30	Surgical data science: open challenges to translate theory into clinical practice	Prof. Paolo Fiorini, University of Verona and Prof. Pierre Jannin, University of Rennes
09.30 - 10,00	Historical review and robotically assisted partially autonomous kidney surgery resection in phantom models	Kevin Cleary, The Sheikh Zayed Institute for Pediatric Surgical Innovation, Children's National Hospital
10.00 - 10.30	Poster teaser
10:30 - 11:00	Coffee Break
11.00 - 11.30	World Café-discussion: How Surgical Data Science in Robotic surgery can benefit the surgical team?
11.30 - 12.00	Towards natural cooperation with cognitive surgical robotics	Prof. Franziska Mathis Ullrick, Erlangen
12.00 - 12.30	Predictive Modeling of Surgical Team's Cognitive Workload with Deep Learning.	Prof. Marco Zenati, Harvard University
12:30 - 13:30	Lunch Break
13.30 - 14.00	How Surgeon-Machine Collaboration can benefit the patient	Dr. Micha Pfeiffer, University of Dresden
14.00 - 14.30	Surgical Data Science: Optimising the delivery of interventional healthcare	Prof. Evangelos Mazomenos, University College London
14.30 - 15.00	World Café-discussion: How Surgical Data Science in Robotic surgery can benefit the patient?
15:00 - 15:30	Coffee Break
15.30 - 16.00	Robotic-surgery procedural knowledge extraction from text using LLMs	Dr. Marco Bombieri, University of Verona
16.00 - 16.30	Cognitive Vision for Surgical Guidance during Cancer Resection	Prof. Stamatia Giannarou, Imperial College
16.30 - 17.00	Round Table
17:00	Workshop End

Key Topics

Multimodal analysis of surgical data captured before and during the surgery
Possible applications of surgical data science in robotic-surgery
Techniques for robotic-surgical workflow generation using surgical data science
Certification of correctness and safety of robotic modules based on surgical data science

Learning Outcomes

Understanding of surgical data science state-of-the-art techniques
Understanding of the state-of-the-art techniques in multimodal data analysis
Analysis of the gaps that hamper the application of surgical data science methods to robotics.
Exploration of ethical and governance challenges associated to the use of data in surgery
Explainability in AI models used in surgical data science
Review and discussions of strategies for certifiability of robotic modules based on surgical data science
Discuss the future directions, potential advancements, and challenges of surgical data science in robotics
Discussion with experts and opportunity to establish new scientific collaborations