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Artificial Intelligence in Surgery

Author: Agilandiswari Arumuga Jothi, University of Glasgow, Year 3


Artificial Intelligence, AI, is ascribed to provide a scientific definition that implies giving meaning to the branch in computer science whereby the capability of machines to understand and reasoning of data, as well as applying data acquired from analysis through learning and owing up to adaptations done in circumstances. Computers are also known as machines which had honed their purpose to function upon superhuman competence with the mind-

blowing advances in software programming, processing speed and capacity (1). AI has been predicted to create a change in the tech world by setting up transformation in global productivity, working patterns, and lifestyles. More explicitly, AI in the healthcare sector have a primary concern with the inclusion of AI programs that bring about diagnosis and make therapeutic recommendations

(2). AI in healthcare typically in the surgical sector will lead to groundbreaking changes in terms of medicine.


Futuristic autonomous surgical bots harness the ability to perceive, think, and act

accordingly without active human intervention to attain a pre-determined surgical goal with fewer concerns about safely performing them and effectively enhancing the degree of automation. There are however 3 variables better known as parameters that need to be addressed when it comes to defining the minimally invasive procedures performed by surgical bots, whereby mission complexity, environmental factors, and human intervention (3). In order to get this working, the surgical bot has integrated visual and physical sensors that perceive the environment, a focal processor that centres on receiving sensory input and calculates yields, and mechanical actuators that grant physical task completion. A clinically viable and versatile autonomous gadget will require an impressive turn of events and considerable development with the enhancement in control

algorithms, robotics, computerized sensory vision and smart sensor tech to tackle challenges such as the deformable nature of the soft tissue environment, the existence of hollow organs that are much vulnerable to rupture and fragility of tissues (3).


General surgery is conceivably the best-known intervention for surgical robots. There has been a drift towards a less invasive procedure in general surgery with a high inclination to the use of laparoscopic and robotic intervention in surgery. Hence the development and improvisation done to robotic-assisted systems to overcome the limitations of existing models to minimize surgical burdens and at the same time enhance the capabilities of surgeons (4). Despite, automation in robotic surgery that comes with a multitude of benefits, robotic catheter

navigation has remarked its place as being the widely used medical instrument to conduct surgical intervention within the heart or blood vessels. Harmful X-rays are a downside when they can be exposed to surgeons where catheter ablation procedures require a wire to be pushed with manual steps and thus to address this stumbling block, robotic systems for catheter navigation have will in deed will be advantageous in eliminating the need to manually manipulate the wire.

In addition, surgeons are enabled to toy with the robot-assisted device remotely, thereby minimizing the exposure to radiation inflicted upon them (5).


As we are transcending from the age of information to the age of Artificial Intelligence surgeons need to be conversant with the advantages and disadvantages of the processes orchestrated by the AI. The realization of clinically viable surgical robots powered by AI are already being augmented to continuously optimize surgical capability and its outcome as well as heighten the access to care. It is imperative to hack back to the notion where AI is not a panacea and requires human oversight. The nature of some complex algorithms can place obscurity to the rationale for outputs and can be “black box” which would call for the rationale for the outputs gained is mysterious to both surgeons, physicians and engineers who built it (6). Hence, the engagement of medical practitioners to shared decision-making with their patients by means of inputting data in the form of risk and reward from AI processing to enhance clinical judgement. By incorporating AI into clinical training and research, surgeons around the world will be highly equipped with the vast knowledge, tools and the untapped skills to enhance patient care.


References

1. Liang X, Yang X, Yin S, Malay S, Chung K, Ma J et al. Artificial Intelligence in Plastic

Surgery: Applications and Challenges. Aesthetic Plastic Surgery. 2020;. doi:

10.1007/s00266-019-01592-2

2. Esteva H, Núñez T, Rodríguez R. Neural Networks and Artificial Intelligence in Thoracic

Surgery. Thoracic Surgery Clinics. 2007;17(3):359-367. doi:

10.1016/j.thorsurg.2007.07.012

3. Panesar S, Cagle Y, Chander D, Morey J, Fernandez-Miranda J, Kliot M. Artificial

Intelligence and the Future of Surgical Robotics. Annals of Surgery. 2019;270(2):223-

226. doi: 10.1097/sla.0000000000003262

4. Simorov A, Otte R, Kopietz C, Oleynikov D. Review of surgical robotics user interface:

what is the best way to control robotic surgery?. Surgical Endoscopy. 2012;26(8):2117-

2125. doi: 10.1007/s00464-012-2182-y

5. Innovations in Robotic Surgery 2020-2030: Technologies, Players & Markets

6. Cabitza F, Rasoini R, Gensini GF. Unintended consequences of machine learning in

medicine. 2017:. JAMA 318:517–518

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