The state-of-the-art in Surgery AI (SAI) is rapidly evolving and showing great promise. AI/ML driven tools and processes are expanding their footprint in a variety of surgical specialties, including general surgery, head and neck surgery, ophthalmology, cardiothoracic surgery, and vascular surgery, to name a few. In recent years, we have seen AI make its way into the operating theaters. Though it has not yet been able to replace the surgeon, it has the potential to become a highly valuable surgical tool. Key advances in the field include AI involvement in preoperative planning, intraoperative assistance, postoperative care and outcome prediction, and education and training of future surgeons. In Preoperative Planning, AI is being used to analyze patient data and imaging, helping surgeons plan procedures more accurately, ultimately promising better outcomes and reduced surgery times. In intraoperative assistance during surgery, AI can provide real-time data and guidance, helping surgeons make more informed decisions. This includes tools like computer navigation and robotic assistance. In postoperative care, AI can help monitor patients after surgery, predicting potential complications and suggesting interventions which can improve recovery times and reduce readmission rates. Finally, in education and training, AI driven simulations and virtual reality environments for practice can help current and next generation of surgeons in utilizing these technologies. Overall, AI is enhancing every stage of surgical care, and this is an exciting time for the field.

Topics of interest

Example areas include but are not limited to:

  • Preoperative Planning with AI 
  • Intraoperative Assistance 
  • Real-time AI tools, including robotics, for surgical procedure guidance 
  • Postoperative Care 
  • Surgical outcome and complication prediction 
  • Surgical Training and Simulation 
  • Ethical considerations in surgery AI 
  • AI in Minimally Invasive Surgery 
  • Precision AI in surgery 
  • AI-Driven Predictive Modeling and path planning 
  • System Implementation, Integrating AI tools into surgery 
  • Multimodal Imaging Guidance

Expected types of contributions

  • Regular papers: The length of the contribution is limited to 6 pages, but it is possible to extend the paper length up to 8 pages by paying for each extra page. Check fees for more information.
  • Short papers: The length of the contribution is limited to 4 pages and no less than 3 pages, not being possible to extend the paper length. The duration of the oral presentation of short posters will be less than regular ones.

More information available at: https://2025.cbms-conference.org/

Organizers

  • Sameer Antani, National Institutes of Health, USA 
  • Sudanthi Wijewickrema, The University of Melbourne, Australia
  • Sharib Ali, University of Leeds, UK 

Program Committee

  • Kh Tohidul Islam, Monash University, Australia 
  • Jan Margeta, KardioMe, Slovakia 
  • Yuansan Liu, Melbourne University, Australia
  • Raabid Hussain, Cochlear, France 
  • Zhiyun Xue, National Library of Medicine, USA 
  • Sivaramakrishnan Rajaraman, National Library of Medicine, USA 
  • Zhaohui Liang, National Library of Medicine, USA 
  • Niccolo Marini, National Library of Medicine, USA 
  • Henning Müller, HES-SO Valais, Switzerland

Contact

For more information, please visit the IEEE CBMS 2025 website at https://2025.cbms-conference.org/ or contact the track chairs at sameer [dot] antani [at] nih [dot] gov.

Call for papers

You can download Call for papers here.