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Selected Publication:
SHR Neuro Cancer Cardio Lipid Metab Microb
O'Sullivan, S; Leonard, S; Holzinger, A; Allen, C; Battaglia, F; Nevejans, N; van Leeuwen, FWB; Sajid, MI; Friebe, M; Ashrafian, H; Heinsen, H; Wichmann, D; Hartnett, M; Gallagher, AG.
Operational framework and training standard requirements for AI-empowered robotic surgery.
Int J Med Robot. 2020; 16(5):1-13
Doi: 10.1002/rcs.2020
Web of Science
PubMed
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- Co-authors Med Uni Graz
- Holzinger Andreas
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- Abstract:
- 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. 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. 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. © 2020 John Wiley & Sons Ltd.
- Find related publications in this database (Keywords)
- surgical skills
- dexterity
- autonomous robotic surgery
- supervised autonomy
- explainable artificial intelligence xai
- surgical navigation