Abstract
To the Editor,
We have read with interest the recent article published by Veilleux et al. 1 and we congratulate them for such a stimulating article. Obesity rates continue rising around the world with an alarming number up to 650 million.
In the era of evidence-based medicine, we need to measure our performance in a manner that allows us to make the best decisions, as stated in this article and in the consensus article on robotics in general surgery promoted by the European Association for Endoscopic Surgery (EAES); the amount and quality of evidence published regarding robotic surgery to our current dates is insufficient. 2 Classical comparison between robotic and laparoscopic surgery is made, and unfortunately, we continue evaluating classical outcomes of morbimortality and cost.
However, the query on the field would be after >30 years of the inception minimal invasiveness concept and data acquisition, in which robotic has become a crown jewel for surgical evolution in the past 20 years: why are we still evaluating techniques by the same principles we have already done?
A surgeon's decisions are derived from complex previous experiences combined with real sensorial conditions during procedures. However, how many previous experiences does a surgeon require to both complete training and possess advanced skills in complex surgical decisions? Can we integrate not just our experience in the surgical field? 3
Development of Big Data defined as the set of data so large that traditional data processing applications are not enough to deal with them, this include the digital data obtained from multiple sources text, data base, and medical records. Robotic surgery has an important role in the Big Data acquisition and consequently in new support actions to conduct surgery. 4
It is, in essence, the democratization of surgery, while you are operating is providing you the vast type of information that will help you and all surgical community to decide in the future.
Artificial intelligence (AI) consists of algorithms which enable a machine's ability for cognitive patterns of problem solving. In this era of digital revolution, understanding these patterns in real cases, logistic steps in instrument utilization, and determining correct decisions for patient care is crucial.
The University of Harvard in the past 6 years has developed computer vision models important core subfield of the AI in the operating room to really understand the concept of what is happening in the course of the operation and how this might affect the patient outcome. With real-time comparison the sequence of frames and plots probability of certain side effects, as we can see robotic field is still unfolding and artificial interface is part of the present and future of surgery.5,6
Currently, the da Vinci™ system (Intuitive Surgical, Sunnyvale, CA) is the most used robotic platform. However, Intuitive patents will expire in the next years and new platforms will arrive on the market, including Transenterix Senhance™ (Morrisville, NC), Versius Cambridge Medical Research (Cambridge, United Kingdom), VerbSurgical (partnership between Google and Johnson & Johnson VerbSurgical, Inc., Bayshore, CA), and Medtronic's Hugo RAS System (Minneapolis, MN). These will allow for expanded robotic surgery options.
It is evident that this Big Data will need a proper way to be shared and that robotic surgery will not offer full advantage until 5G enables the use without geographic limitation. This type of transmission has high cost due to infrastructure investment, but surgery has already been demonstrated in a veterinarian remote brain surgery recently in China. 7
Even if we see it as a distant path to walk, it is not far away; we must open our minds and promote our colleagues to produce better research with the vision of developing prediction models and algorithms in the most accurate manner. The upcoming robotic surgery implementation with telesurgery will become as commonplace as navigating the Internet on wireless networks, which Nikola Tesla had predicted many years before through his vision of wireless energy and data transmission. Integration of Big Data and AI will lead us to the next surgical revolution. 8
“The important thing in science is not so much to obtain new facts as to discover new ways of thinking about them.”