Operational framework and training standard requirements for AI-empowered robotic surgery
| Autor: | Dominic Wichmann, Margaret Hartnett, Fijs W. B. van Leeuwen, Nathalie Nevejans, Shane O'Sullivan, Andreas Holzinger, Colin Allen, Fiorella Battaglia, Anthony G. Gallagher, Hutan Ashrafian, Michael Friebe, Mohammed Imran Sajid, Helmut Heinsen, Simon Leonard |
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| Přispěvatelé: | O( extquotesingle)Sullivan, Shane, Leonard, Simon, Holzinger, Andrea, Allen, Colin, Battaglia, Fiorella, Nevejans, Nathalie, van Leeuwen, Fijs W. B., Imran Sajid, Mohammed, Friebe, Michael, Ashrafian, Hutan, Heinsen, Helmut, Wichmann, Dominic, Hartnett, Margaret, Gallagher, Anthony G. |
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
Robotic Surgical Procedure
medicine.medical_specialty Computer science 0206 medical engineering Biophysics 02 engineering and technology surgical navigation Machine Learning 03 medical and health sciences autonomous robotic surgery 0302 clinical medicine Molecular level Robotic Surgical Procedures Artificial Intelligence medicine explainable artificial intelligence xai Humans Medical physics Robotic surgery 030212 general & internal medicine Medical imaging data supervised autonomy Surgical robotics Surgeons Robotics 020601 biomedical engineering Robotic Computer Science Applications dexterity Transparency (graphic) surgical skill surgical skills Operational framework Gross anatomy Surgery Metric (unit) Human |
| Zdroj: | International Journal of Medical Robotics and Computer Assisted Surgery, 16(5). WILEY |
| Popis: | Background For autonomous robot-delivered surgeries to ever become a feasible option, we recommend the combination of human-centered artificial intelligence (AI) and transparent machine learning (ML), with integrated Gross anatomy models. This can be supplemented with medical imaging data of cadavers for performance evaluation. Methods We reviewed technological advances and state-of-the-art documented developments. We undertook a literature search on surgical robotics and skills, tracing agent studies, relevant frameworks, and standards for AI. This embraced transparency aspects of AI. Conclusion We recommend "a procedure/skill template" for teaching AI that can be used by a surgeon. Similar existing methodologies show that when such a metric-based approach is used for training surgeons, cardiologists, and anesthetists, it results in a >40% error reduction in objectively assessed intraoperative procedures. The integration of Explainable AI and ML, and novel tissue characterization sensorics to tele-operated robotic-assisted procedures with medical imaged cadavers, provides robotic guidance and refines tissue classifications at a molecular level. |
| Databáze: | OpenAIRE |
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