2nd Workshop on Machine Learning in Medical Robotics: Bridging ML Theory and Clinical Frontiers

October 14, 2024, 14:00-18:00, Abu Dhabi, UAE

Website: https://sites.google.com/view/rolemap-iros2024

Scope

Machine learning (ML) holds transformative potential for revolutionizing medical robotics research, thereby significantly enhancing surgery and rehabilitation practices. The rapid advancements in ML have led to the proposal of numerous innovative algorithms. Despite the promise of the AI era, its full benefits have yet to be fully leveraged in medical robotics. This shortfall stems from a few key issues: a lack of awareness among medical roboticists about the capabilities of each ML algorithm; insufficient collaboration between medical robotics and computer science experts; and stringent safety and interpretability requirements for healthcare applications, which complicate the adoption of ML technologies. This workshop acts as a nexus between theoretical ML and clinical frontiers, fostering dialogue among medical robotics engineers, ML/robot learning researchers, and clinicians.

Topics of interests

This workshop will specifically focus on advancements in ML techniques and the latest developed algorithms for medical robots’ perception, modeling, control, and navigation around the following key themes:

• Advancements in autonomous robotics surgery
• ML in medical robotics modeling
• Learning of surgical skills from demonstrations/videos
• Medical robot sensing and localization based on ML
• Applications of generative AI and Large Language Models (LLM) in medical robotics
• Autonomous (sub-)task learning and execution
• Data-driven simulations for surgical training
• …

Submission Guidelines - Call For Abstracts

The workshop is calling extended abstracts. To participate, please submit an extended abstract (max 2 pages) as a PDF in the standard IEEE conference format. Before the workshop, authors of the accepted posters are required to submit a one-page PPT to the organizer, and they will have 3 minutes to introduce their work at the workshop.

Three Best Paper Awards will be selected. Authors of the winning original papers will be invited to submit an extended version of their work for inclusion in a forthcoming Special Issue of a journal.

Organizing Committees

• Jing Guo, Guangdong University of Technology, China
• Di Wu, KU Leuven, Belgium
• Loris Fichera, Worcester Polytechnic Institute, USA
• Farshid Alambeigi, University of Texas at Austin, USA
• Yao Zhang, KU Leuven, Belgium
• Michael Yip, University of California at San Diego, USA

Contact

All questions about submissions should be emailed to di.wu@kuleuven.be