Development of artificial intelligence technology in diagnosis, treatment, and prognosis of colorectal cancer

Abstract

Artificial intelligence (AI) technology has made leaps and bounds since its invention. AI technology can be subdivided into many technologies such as machine learning and deep learning. The application scope and prospect of different technologies are also totally different. Currently, AI technologies play a pivotal role in the highly complex and wide-ranging medical field, such as medical image recognition, biotechnology, auxiliary diagnosis, drug research and development, and nutrition. Colorectal cancer (CRC) is a common gastrointestinal cancer that has a high mortality, posing a serious threat to human health. Many CRCs are caused by the malignant transformation of colorectal polyps. Therefore, early diagnosis and treatment are crucial to CRC prognosis. The methods of diagnosing CRC are divided into imaging diagnosis, endoscopy, and pathology diagnosis. Treatment methods are divided into endoscopic treatment, surgical treatment, and drug treatment. AI technology is in the weak era and does not have communication capabilities. Therefore, the current AI technology is mainly used for image recognition and auxiliary analysis without in-depth communication with patients. This article reviews the application of AI in the diagnosis, treatment, and prognosis of CRC and provides the prospects for the broader application of AI in CRC.

Application of artificial intelligence in diagnosis and treatment of colorectal cancer: A novel Prospect

“…Without a large amount of high-quality data as the basis, even the most advanced algorithm model will not help. Therefore, we urgently need to standardize big medical data and increase interoperability among multiple centers ( 90 , 147 , 156 ). Moreover, there are specific problems in various imaging omics and AI models.…”

“…Experiments have confirmed that the da Vinci SP system is an excellent model for taTME and natural orifice specimen extraction ( 139 , 145 , 146 ). One of the biggest problems of robotic surgery is the high cost ( 145 , 147 ). It indicates that the promotion of robotic surgery requires government financial support.…”

Role of artificial intelligence in risk prediction, prognostication, and therapy response assessment in colorectal cancer: current state and future directions

“…Another issue with the clinical application of AI and ML is the “black box” problem, in which we are able to see the inputs and outputs of a model, but not the variables that are used by the model to generate those outputs. More efforts are needed to make the algorithms, especially deep learning algorithms, interpretable to clinicians and to allow streamlining of data preprocessing ( 114 ). Additionally, most of the studies have a retrospective design, and more evidence on the effectiveness of AI is needed from multicenter, prospective studies.…”

Future of Artificial Intelligence Applications in Cancer Care: A Global Cross-Sectional Survey of Researchers

“…For example, as a predictive modeling and early detection, AI could be used to analyze data from a variety of sources, such as electronic health records, genetic information, and environmental data, to predict an individual’s risk of developing cancer and to tailor prevention strategies accordingly [ 13 , 14 , 15 , 16 ]. AI-related applications may reduce screening costs [ 17 ], provide more reliable diagnostics [ 13 , 18 , 19 , 20 ], improve prognostics [ 13 , 19 , 21 , 22 , 23 , 24 , 25 ], and aid in the discovery of new drugs [ 14 , 15 ]. Several areas of cancer care are expected to benefit from AI-related applications, including cancer radiology and clinical oncology [ 10 ].…”