SAIIL focuses on developing innovative computer vision technologies in Surgery, enabling physician cognitive augmentation to democratize knowledge, improve surgical outcomes, lower costs, and enhance surgeons’ experience.

The development and implementation of surgical AI offer various research opportunities, including:

  1. Expanding AI Applications: Investigating novel ways to apply AI techniques, such as machine learning and computer vision, to surgical processes and procedures, with a focus on real-time support and clinical intervention.

  2. Dataset Collection and Standardization: Developing standardized protocols for surgical video annotation, data collection, and sharing to facilitate developing and validating AI applications in surgery.

  3. Multidisciplinary Collaboration: Fostering collaboration between researchers, surgeons, and AI experts to develop innovative solutions, validate applications, and establish best practices for the integration of AI in surgery.

  4. Ethics and Policy: Addressing legal, ethical, and societal challenges surrounding the collection of surgical data, patient privacy, and AI deployment in healthcare.

  5. Evaluation and Validation: Conducting rigorous evaluation and validation of AI applications in surgery to ensure their effectiveness, safety, and utility in improving patient care and outcomes.

Our Projects and Publications

  • Surgical Fingerprints

    Computational Collective Surgical Consciousness

    SleeveNet

    POEMNet

  • The SAGES Critical View of Safety Challenge

Publications

  1. Eckhoff, J. A., Y. Ban, G. Rosman, D. T. Müller, D. A. Hashimoto, E. Witkowski, B. Babic et al. "TEsoNet: knowledge transfer in surgical phase recognition from laparoscopic sleeve gastrectomy to the laparoscopic part of Ivor–Lewis esophagectomy." Surgical Endoscopy (2023): 1-14.

  2. Eckhoff, Jennifer A., Hans F. Fuchs, and Ozanan R. Meireles. "Application of artificial intelligence in oncologic surgery of the upper gastrointestinal tract." ONKOLOGIE (2023).

  3. ​​Ban, Y., Eckhoff, J. A., Ward, T. M., Hashimoto, D. A., Meireles, O. R., Rus, D., & Rosman, G. (2022). Concept graph neural networks for surgical video understanding. arXiv preprint arXiv:2202.13402.

  4. Ban, Yutong, Guy Rosman, Jennifer A. Eckhoff, Thomas M. Ward, Daniel A. Hashimoto, Taisei Kondo, Hidekazu Iwaki, Ozanan R. Meireles, and Daniela Rus. "Supr-gan: surgical prediction gan for event anticipation in laparoscopic and robotic surgery." IEEE Robotics and Automation Letters 7, no. 2 (2022): 5741-5748.

  5. Ban, Y., Li, X., Rosman, G., Gilitschenski, I., Meireles, O., Karaman, S., & Rus, D. (2022, May). A deep concept graph network for interaction-aware trajectory prediction. In 2022 International Conference on Robotics and Automation (ICRA) (pp. 8992-8998). IEEE.

  6. Ward, Thomas M., Daniel A. Hashimoto, Yutong Ban, Guy Rosman, and Ozanan R. Meireles. "Artificial intelligence prediction of cholecystectomy operative course from automated identification of gallbladder inflammation." Surgical Endoscopy 36, no. 9 (2022): 6832-6840.

  7. Ward, T.M., Hashimoto, D.A., Ban, Y., Rattner, D.W., Inoue, H., Lillemoe, K.D., Rus, D.L., Rosman, G. and Meireles, O.R., 2020. Automated operative phase identification in peroral endoscopic myotomy. Surgical Endoscopy, pp.1-8.

  8. Ward, T.M., Mascagni, P., Madani, A., Padoy, N., Perretta, S. and Hashimoto, D.A., 2021. Surgical data science and artificial intelligence for surgical education. Journal of Surgical Oncology, 124(2), pp.221-230.

  9. Meireles, O.R., Rosman, G., Altieri, M.S., Carin, L., Hager, G., Madani, A., Padoy, N., Pugh, C.M., Sylla, P., Ward, T.M. and Hashimoto, D.A., 2021. SAGES consensus recommendations on an annotation framework for surgical video. Surgical endoscopy, pp.1-12.

  10. Hashimoto, D.A., 2021. Surgeons and Machines can Learn from Operative Video: Will the System let Them?. Annals of Surgery, 274(1), p.e96.

  11. Wong, D.J., Miranda-Nieves, D., Nandivada, P., Patel, M.S., Hashimoto, D.A., Kent, D.O., Gómez-Márquez, J., Lin, S.J., Feldman, H.J. and Chaikof, E.L., 2021. The Surgical Program in Innovation (SPIN): A Design and Prototyping Curriculum for Surgical Trainees. Academic Medicine.

  12. Madani, A., Namazi, B., Altieri, M.S., Hashimoto, D.A., Rivera, A.M., Pucher, P.H., Navarrete-Welton, A., Sankaranarayanan, G., Brunt, L.M., Okrainec, A. and Alseidi, A., 2021. Artificial intelligence for intraoperative guidance: using semantic segmentation to identify surgical anatomy during laparoscopic cholecystectomy. Annals of Surgery.

  13. Ward, T.M., Mascagni, P., Ban, Y., Rosman, G., Padoy, N., Meireles, O. and Hashimoto, D.A., 2021. Computer vision in surgery. Surgery, 169(5), pp.1253-1256.

  14. Garrow, C.R., Kowalewski, K.F., Li, L., Wagner, M., Schmidt, M.W., Engelhardt, S., Hashimoto, D.A., Kenngott, H.G., Bodenstedt, S., Speidel, S. and Müller-Stich, B.P., 2021. Machine learning for surgical phase recognition: a systematic review. Annals of Surgery, 273(4), pp.684-693.

  15. Ward, T.M., Fer, D.M., Ban, Y., Rosman, G., Meireles, O.R. and Hashimoto, D.A., 2021. Challenges in surgical video annotation. Computer Assisted Surgery, 26(1), pp.58-68.

  16. Ban, Y., Rosman, G., Ward, T., Hashimoto, D., Kondo, T., Iwaki, H., Meireles, O. and Rus, D., 2020. Aggregating Long-Term Context for Learning Laparoscopic and Robot-Assisted Surgical Workflows. International Conference on Robotics and Automation (ICRA) 2021. 

  17. Hashimoto, D.A., Witkowski, E., Gao, L., Meireles, O. and Rosman, G., 2020. Artificial intelligence in anesthesiology: current techniques, clinical applications, and limitations. Anesthesiology, 132(2), pp.379-394.

  18. Hashimoto, D.A., Rosman, G., Rus, D. and Meireles, O.R., 2018. Artificial intelligence in surgery: promises and perils. Annals of surgery, 268(1), p.70.

  19. Hashimoto, D.A., Rosman, G., Witkowski, E.R., Stafford, C., Navarrete-Welton, A.J., Rattner, D.W., Lillemoe, K.D., Rus, D.L. and Meireles, O.R., 2019. Computer vision analysis of intraoperative video: automated recognition of operative steps in laparoscopic sleeve gastrectomy. Annals of surgery, 270(3), p.414.