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Page 6 of 16 Nawrat. Mini-invasive Surg 2020;4:28 I http://dx.doi.org/10.20517/2574-1225.2020.08

Figure 1. Virtual operating room made in FRK (in a team led by the author). It is used for planning operations using Robin Heart robots
(examples are for heart surgery) and for testing robots (in the conceptual phase) and training surgeons. The developed program in virtual
space technology was tested for use: (1) on a computer stand; (2) in the Robin Heart Shell 2 robot control console; (3) VR goggles (Oculus).
The images below are examples of how to visualize simulated operations. The last image outlines the green work space available for the
tool chosen by the surgeon

This means that we can enrich the image with prognostic information. Moreover, if we introduce an image
analysis system of the operations performed by a surgeon, we can modify it to keep up with the effects of
surgery. This is one of the aims of my research work in my Fundacja Rozwoju Kardiochirurgii (FRK) team.

However, this is still not putting AI into surgery. We have known for many years that we can use
telemedicine systems for consulting and verification of the correctness of actions taken by a teacher surgeon
who is located away from the operating room. The endoscopic track can be connected to a conference
room where all participants can comment live on the operation which is performed in the hospital.

Telemedicine systems are successfully used when, for example, the surgeon has to undertake very
little surgery, which is unusual for the practice, but in this way can use the advice directly from a more
experienced specialist. In the information exchange system, we thus turn on the brain of another person
who does not physically participate directly in the operation. However, if we imagine that we can model on-
line surgery in a digital, computer (simulation) or physical (modeling) system and thus create possibilities
for the history of operations by forecasting the results of subsequent steps taken by the doctor, we are then
building a very advanced advisory system based on experimental facts (model). If the model is perfect
(which is extremely difficult for physiological models) then we will get excellent advice. We can also base
our advice for the surgeon on the analysis of real data, from real operations, i.e., Big Data analysis. In this
way, we can build a very advanced advisory system based on medical facts. Clearly, this reasoning seeks
to demonstrate that the combination of these approaches can be a breakthrough in the quality of advisory
systems. The systems supporting the real surgeon while making decisions should graphically indicate the
location, place of intervention and provide biological-chemical-physical data that is both current and
forecasted based on a specific selection of tactics.