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Wang WA, Dong P, Zhang A, Wang WJ, Guo CA, Wang J, Liu HB. Artificial intelligence: A new budding star in gastric cancer. Artif Intell Gastroenterol 2020; 1:60-70. [DOI: 10.35712/aig.v1.i4.60] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 11/01/2020] [Accepted: 11/27/2020] [Indexed: 02/06/2023] Open
Abstract
The pursuit of health has always been the driving force for the advancement of human society, and social development will be profoundly affected by every breakthrough in the medical industry. With the arrival of the information technology revolution era, artificial intelligence (AI) technology has been rapidly developed. AI has been combined with medicine but it has been less studied with gastric cancer (GC). AI is a new budding star in GC, and its contribution to GC is mainly focused on diagnosis and treatment. For early GC, AI’s impact is not only reflected in its high accuracy but also its ability to quickly train primary doctors, improve the diagnosis rate of early GC, and reduce missed cases. At the same time, it will also reduce the possibility of missed diagnosis of advanced GC in cardia. Furthermore, it is used to assist imaging doctors to determine the location of lymph nodes and, more importantly, it can more effectively judge the lymph node metastasis of GC, which is conducive to the prognosis of patients. In surgical treatment of GC, it also has great potential. Robotic surgery is the latest technology in GC surgery. It is a bright star for minimally invasive treatment of GC, and together with laparoscopic surgery, it has become a common treatment for GC. Through machine learning, robotic systems can reduce operator errors and trauma of patients, and can predict the prognosis of GC patients. Throughout the centuries of development of surgery, the history gradually changes from traumatic to minimally invasive. In the future, AI will help GC patients reduce surgical trauma and further improve the efficiency of minimally invasive treatment of GC.
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Affiliation(s)
- Wen-An Wang
- Graduate School, Gansu University of Traditional Chinese Medicine, Lanzhou 730000, Gansu Province, China
- Department of General Surgery, The 940th Hospital of Joint Logistics Support Force of Chinese People’s Liberation Army, Lanzhou 730050, Gansu Province, China
| | - Peng Dong
- Department of General Surgery, Lanzhou University Second Hospital, Lanzhou 730000, Gansu Province, China
| | - An Zhang
- Graduate School, Gansu University of Traditional Chinese Medicine, Lanzhou 730000, Gansu Province, China
- Department of General Surgery, The 940th Hospital of Joint Logistics Support Force of Chinese People’s Liberation Army, Lanzhou 730050, Gansu Province, China
| | - Wen-Jie Wang
- Department of General Surgery, Lanzhou University Second Hospital, Lanzhou 730000, Gansu Province, China
| | - Chang-An Guo
- Department of Emergency Medicine, Lanzhou University Second Hospital, Lanzhou 730000, Gansu Province, China
| | - Jing Wang
- Graduate School, Gansu University of Traditional Chinese Medicine, Lanzhou 730000, Gansu Province, China
- Department of General Surgery, The 940th Hospital of Joint Logistics Support Force of Chinese People’s Liberation Army, Lanzhou 730050, Gansu Province, China
| | - Hong-Bin Liu
- Department of General Surgery, The 940th Hospital of Joint Logistics Support Force of Chinese People’s Liberation Army, Lanzhou 730050, Gansu Province, China
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