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Page 396 Sadagopan et al. Art Int Surg 2024;4:387-400 https://dx.doi.org/10.20517/ais.2024.34

Table 4. Levels of automation in spine surgery
Level Description Example Device
0 Manual Freehand pedicle screw placement Standard surgical tools
1 Computer-assisted Neuronavigation RONNA
navigation
2 Task-specific automation Robot-assisted pedicle screw placement DLR Light-Weight Robot
LWR-II
3 Semi-autonomous spine Autonomous laminectomy with surgeon oversight AUBO-i5 robot with SRI
surgery force sensor
4 Highly autonomous spine Complete autonomy over all surgical steps (initial exposure, fusion, closure) Not yet developed
surgery with some surgeon oversight
5 Fully autonomous spine No human surgeon intervention Not yet developed
surgery

RONNA: Robotic neuronavigation.

these novel surgical systems. This classification can serve as a guideline for stratifying the emerging
technologies that are specific to the challenges and complexities of spine surgery.

Benefits of surgical automation
The standardization of surgical techniques through automation and AI reduces variation in clinical
outcomes and enhances precision. By leveraging algorithms and robotic systems, surgical procedures can be
executed with increased accuracy, leading to fewer errors and improved patient outcomes [41,42] . Automation
enables the execution of predefined strategies with consistency, minimizing the influence of human factors
and ensuring reproducibility across different surgical settings.

The adoption of automation in surgery allows for the increased bandwidth of surgical staff to focus on
human needs. By offloading repetitive and mundane tasks to automated systems, surgical teams can redirect
their attention toward providing personalized care, communicating with patients and their families, and
addressing the emotional and psychological aspects of the surgical experience. This shift in focus toward
patient-centered care fosters a more holistic approach to healthcare delivery, promoting better overall
patient satisfaction and well-being.

Incorporating preoperative and intraoperative monitoring enhances surgical precision and safety . AI-
[43]
driven algorithms analyze imaging data in real time, providing surgeons with detailed insights into patient
anatomy and pathology, facilitating informed decision making during surgery. Additionally, the integration
of preoperative and intraoperative variables enables the early recognition and mitigation of postoperative
complications, morbidity, and mortality.

In high-complexity scenarios, where surgeons’ decision-making capacity may be compromised due to stress
or cognitive overload, automation may be preferable. Automated systems can execute predefined surgical
strategies and adapt to rapidly changing conditions, ensuring timely and effective interventions even in the
most challenging circumstances . By augmenting surgeons’ capabilities with AI-driven technologies, the
[10]
risk of errors and adverse events can be minimized, ultimately improving success rates.

[44]
Integrating automation and AI with big data analytics holds the potential for advancing surgical practice .
By harnessing vast amounts of patient data, including demographic information, clinical histories, and
treatment outcomes, AI algorithms can identify patterns, predict patient responses to treatment, and
optimize surgical strategies. This integration enables personalized healthcare delivery and informs