Colorectal cancer: Artificial intelligence and its role in surgical decision making

Table 1 Subfields of artificial intelligence and its application in day-to-day human life

S. No	Fields of AI	Description
1	Machine learning	Pattern identification and analysis where machine can help to improve based on past experiences provided from the given data set
2	Deep learning	Consists of multilayered neural networks called artificial neural network, which enables the computer to learn and make decisions on its own
3	Natural language processing	Ability of the computer to extract data from human language and make decisions
4	Computer vision	Potential to obtain information from a series of images or videos
5	Mixed-integer linear programming model[11]	It is helpful in finding the locational, supply, production, distribution, collection, quarantine, recycling, reuse, and disposal decisions within a multiperiod multiechelon multiproduct supply chain
6	Covering tour approach[9]	Optimizing the distribution and allocation of resources among individuals. It is useful at the time of crisis
7	Mixed-integer linear mathematical model[6]	This model optimizes economic, social, and environmental objectives simultaneously
8	Neural network with runner root algorithm[8]	Minimizing risk and maximizing return in industrial production
9	Meta-heuristic algorithms[7]	A comprehensive framework to predict the demand for dairy products
10	Hybrid shapley value and multimoora method[10]	An intelligent performance evaluation system for different supply chains in industries

AI: Artificial intelligence; S. No: Serial number.

Table 2 Studies having found the role of artificial intelligence in identification of vital structures in surgery

S. No	Primary aim	AI method used	Ref.
1	Recognition of ureter and uterine artery	Convolutional neural network	Harangi et al[61], 2017
2	Recognition of surgical steps of retinal surgery	Content-based video retrieval system	Quellec et al[62], 2011
3	To define safe dissection plane in robot assisted gastrectomy	Deep learning model based on U-net	Kumazu et al[63], 2021
4	Recurrent laryngeal nerve detection during thyroidectomy	Deep learning computer vision algorithm	Gong et al[64], 2021

AI: Artificial intelligence; S. No: Serial number.

Table 3 Studies of artificial intelligence differentiating normal epithelium from abnormal or malignant cells

S. No	Modality used	Primary aim of study	AI method used	Ref.
1	CEUS	To differentiate glioblastoma from normal tissue	Support vector machines	Ritschel et al[75], 2015
2	OCT	To distinguish parathyroid tissue from thyroid, lymph node, and adipose tissue	Texture feature analysis and back propagation artificial neural network	Hou et al[76], 2017
3	CLE	Normal colonic mucosa from malignant lesion	Fractal analysis and neural network modelling	Ştefănescu et al[77], 2016
4	Hyperspectral imaging	Differentiation of colonic carcinoma from adenoma and healthy mucosa	Artificial neural network	Jansen-Winkeln et al[72], 2021

AI: Artificial intelligence; CEUS: Contrast-enhanced ultrasonography; OCT: Optical coherence tomography; CLE: Confocal laser endomicroscopy; S. No: Serial number.