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Review

Scope of Artificial Intelligence in Gastrointestinal Oncology

1
Department of Internal Medicine, The Wright Center for Graduate Medical Education, 501 S. Washington Avenue, Scranton, PA 18505, USA
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Department of Medicine, John H Stroger Jr Hospital of Cook County, 1950 W Polk St, Chicago, IL 60612, USA
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Department of Medicine, Saint Agnes Medical Center, 1303 E. Herndon Ave, Fresno, CA 93720, USA
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Department of Medicine, Geisinger Wyoming Valley Medical Center, 1000 E Mountain Dr, Wilkes-Barre, PA 18711, USA
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Division of Interventional Oncology & Surgical Endoscopy (IOSE), Parkview Cancer Institute, 11050 Parkview Circle, Fort Wayne, IN 46845, USA
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Department of Gastroenterology and Hepatology, University of Toledo Medical Center, 3000 Arlington Avenue, Toledo, OH 43614, USA
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Division of Gastroenterology and Hepatology, CHI Health Creighton University Medical Center, 7500 Mercy Rd, Omaha, NE 68124, USA
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Department of Medicine, Texas Tech University Health Sciences Center, 3601 4th St, Lubbock, TX 79430, USA
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Department of Gastroenterology and Hepatology, The University of Arkansas for Medical Sciences, 4301 W Markham St, Little Rock, AR 72205, USA
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Division of Gastroenterology, Hepatology & Nutrition, McGovern Medical School, UTHealth, 6410 Fannin, St #1014, Houston, TX 77030, USA
*
Author to whom correspondence should be addressed.
Academic Editors: Andreas Stadlbauer, Anke Meyer-Baese and Max Zimmermann
Cancers 2021, 13(21), 5494; https://doi.org/10.3390/cancers13215494
Received: 21 October 2021 / Accepted: 27 October 2021 / Published: 1 November 2021
(This article belongs to the Collection Artificial Intelligence in Oncology)
Gastrointestinal cancers cause over 2.8 million deaths annually worldwide. Currently, the diagnosis of various gastrointestinal cancer mainly relies on manual interpretation of radiographic images by radiologists and various endoscopic images by endoscopists. Artificial intelligence (AI) may be useful in screening, diagnosing, and treating various cancers by accurately analyzing diagnostic clinical images, identifying therapeutic targets, and processing large datasets. The use of AI in endoscopic procedures is a significant breakthrough in modern medicine. Although the diagnostic accuracy of AI systems has markedly increased, it still needs collaboration with physicians. In the near future, AI-assisted systems will become a vital tool for the management of these cancer patients.
Gastrointestinal cancers are among the leading causes of death worldwide, with over 2.8 million deaths annually. Over the last few decades, advancements in artificial intelligence technologies have led to their application in medicine. The use of artificial intelligence in endoscopic procedures is a significant breakthrough in modern medicine. Currently, the diagnosis of various gastrointestinal cancer relies on the manual interpretation of radiographic images by radiologists and various endoscopic images by endoscopists. This can lead to diagnostic variabilities as it requires concentration and clinical experience in the field. Artificial intelligence using machine or deep learning algorithms can provide automatic and accurate image analysis and thus assist in diagnosis. In the field of gastroenterology, the application of artificial intelligence can be vast from diagnosis, predicting tumor histology, polyp characterization, metastatic potential, prognosis, and treatment response. It can also provide accurate prediction models to determine the need for intervention with computer-aided diagnosis. The number of research studies on artificial intelligence in gastrointestinal cancer has been increasing rapidly over the last decade due to immense interest in the field. This review aims to review the impact, limitations, and future potentials of artificial intelligence in screening, diagnosis, tumor staging, treatment modalities, and prediction models for the prognosis of various gastrointestinal cancers. View Full-Text
Keywords: artificial intelligence; colorectal cancer; gastrointestinal cancer; hepatocellular cancer; pancreaticobiliary cancer; gastric cancer; esophageal cancer artificial intelligence; colorectal cancer; gastrointestinal cancer; hepatocellular cancer; pancreaticobiliary cancer; gastric cancer; esophageal cancer
MDPI and ACS Style

Goyal, H.; Sherazi, S.A.A.; Mann, R.; Gandhi, Z.; Perisetti, A.; Aziz, M.; Chandan, S.; Kopel, J.; Tharian, B.; Sharma, N.; Thosani, N. Scope of Artificial Intelligence in Gastrointestinal Oncology. Cancers 2021, 13, 5494. https://doi.org/10.3390/cancers13215494

AMA Style

Goyal H, Sherazi SAA, Mann R, Gandhi Z, Perisetti A, Aziz M, Chandan S, Kopel J, Tharian B, Sharma N, Thosani N. Scope of Artificial Intelligence in Gastrointestinal Oncology. Cancers. 2021; 13(21):5494. https://doi.org/10.3390/cancers13215494

Chicago/Turabian Style

Goyal, Hemant, Syed A.A. Sherazi, Rupinder Mann, Zainab Gandhi, Abhilash Perisetti, Muhammad Aziz, Saurabh Chandan, Jonathan Kopel, Benjamin Tharian, Neil Sharma, and Nirav Thosani. 2021. "Scope of Artificial Intelligence in Gastrointestinal Oncology" Cancers 13, no. 21: 5494. https://doi.org/10.3390/cancers13215494

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