1. Home
  2. GHOA
  3. The emerging era of artificial intelligence and its role in gastroenterology
Submit manuscript...
eISSN: 2373-6372

Gastroenterology & Hepatology: Open Access

Editorial Volume 14 Issue 2

The emerging era of artificial intelligence and its role in Gastroenterology

Venu M Ganipisetti

Department of Medicine, Presbyterian Hospital, NM, USA

Correspondence: Venu M Ganipisetti, Hospital Medicine, Presbyterian Hospital, Albuquerque, USA

Received: April 21, 2023 | Published: April 24, 2023

Citation: Ganipisetti VM. The emerging era of artificial intelligence and its role in Gastroenterology. Gastroenterol Hepatol Open Access. 2023;14(2):64-65. DOI: 10.15406/ghoa.2023.14.00547

Download PDF

Keywords

Artificial intelligence, Upper endoscopy, Gastroenterology, Ultrasound, Cancer detection, Gastroesophageal reflux disease, Helicobacter pylori, Gastrointestinal bleeding, Inflammatory bowel disease, Chronic atrophic gastritis, pancreatitis, bariatric surgery

Editorial

Artificial intelligence (AI) is evolving into various aspects of our lives, and its influence and utility are also emerging in medicine. AI has the potential to save healthcare costs, increase diagnostic accuracy, predict the prognosis of certain conditions, help with treatment planning, and potentially fill the gap of healthcare personnel shortage. However, it also has the dangers of poor regulation, lack of accountability, misuse, and subsequent risks associated with direct involvement in patient care, and the cost of replacing human jobs. We are currently in an exciting and, at the same time, anxious era due to the enormous potential of AI. 

AI in gastroenterology has already shown the potential of broad applicability in several aspects of the field, including early diagnosis, increasing diagnostic accuracy and risk stratification, treatment planning, outcome, and prognosis prediction of various malignant and nonmalignant gastrointestinal (GI) conditions. Some of the exciting AI applications in gastroenterology include the field of ultrasound and upper endoscopy to improve diagnostic yield,1,2 early detection of cancerous lesions,3-4 management of gastroesophageal reflux disease (GERD),5 Helicobacter Pylori diagnosis6,7 early risk stratification in bleeding patients,8 management of inflammatory bowel disease9,10 early detection of high-risk patients with probability to develop severe pancreatitis after admission11 diagnosis of chronic atrophic gastritis,12,13 early detection of Barrett's esophagus14 classification and differentiation of cystic lesions of the pancreas,15 treatment and prognostication of certain cancers and post bariatric surgery prediction of GERD.16

Despite these advancements, significant challenges remain. These include the need for supervised, regulated extensive studies to assess the safety and potential roadblocks in implementation, cost of implementation, ethical and legal challenges. Further research is needed to determine AI's wide-scale applicability in gastroenterology and ensure its responsible integration into patient care.

Conclusion

AI has the potential to revolutionize the field of gastroenterology. Still, addressing the challenges and risks associated with its implementation is crucial to ensure its safe and effective use. AI can improve patient care and outcomes in gastroenterology and beyond through continued research and more importantly responsible integration.

Acknowledgments

None.

Conflicts of interest

We declare there are no conflicts of interest.

Funding

None.

References

  1. Teh JL, Shabbir A, Yuen S, et al. Recent advances in diagnostic upper endoscopy. World J Gastroenterol. 2020;26(4):433–447.
  2. Liu JQ, Ren JY, Xu XL, et al. Ultrasound–based artificial intelligence in gastroenterology and hepatology. World J Gastroenterol. 2022;28(38):5530–5546.
  3. Hassan C, Spadaccini M, Iannone A, et al. Performance of artificial intelligence in colonoscopy for adenoma and polyp detection: a systematic review and meta–analysis. Gastrointest Endosc. 2021;93(1):77–85.e6.
  4. ​​Calderaro J, Seraphin TP, Luedde T, et al. Artificial intelligence for the prevention and clinical management of hepatocellular carcinoma. J Hepatol. 2022;76(6):1348–1361.
  5. Rogers B, Samanta S, Ghobadi K, et al. Artificial intelligence automates and augments baseline impedance measurements from pH–impedance studies in gastroesophageal reflux disease. J Gastroenterol. 2021;56(1):34–41.
  6. Nakashima H, Kawahira H, Kawachi H, et al. Endoscopic three–categorical diagnosis of Helicobacter pylori infection using linked color imaging and deep learning: a single–center prospective study (with video). Gastric Cancer. 2020;23(6):1033–1040.
  7. Luo Q, Yang H, Hu B. Application of artificial intelligence in the endoscopic diagnosis of early gastric cancer, atrophic gastritis, and Helicobacter pylori infection. J Dig Dis. 2022;23(12):666–674.
  8. Seo DW, Yi H, Park B, et al. Prediction of Adverse Events in Stable Non–Variceal Gastrointestinal Bleeding Using Machine Learning. J Clin Med. 2020;9(8):2603.
  9. Borg–Bartolo SP, Boyapati RK, Satsangi J, et al.  Precision medicine in inflammatory bowel disease: concept, progress and challenges. F1000Res. 2020;9:F1000 Faculty Rev–54.
  10. Da Rio L, Spadaccini M, Parigi TL, et al. Artificial intelligence and inflammatory bowel disease: Where are we going? World J Gastroenterol. 2023;29(3):508–520.
  11. Kui B, Pintér J, Molontay R, et al. Hungarian Pancreatic Study Group. EASY–APP: An artificial intelligence model and application for early and easy prediction of severity in acute pancreatitis. Clin Transl Med. 2022;12(6):e842.
  12. Zhang Y, Li F, Yuan F, et al. Diagnosing chronic atrophic gastritis by gastroscopy using artificial intelligence. Dig Liver Dis. 2020;52(5):566–572.
  13. Luo Q, Yang H, Hu B. Application of artificial intelligence in the endoscopic diagnosis of early gastric cancer, atrophic gastritis, and Helicobacter pylori infection. J Dig Dis. 2022;23(12):666–674.
  14. Spadaccini M, Vespa E, Chandrasekar VT, et al. Advanced imaging and artificial intelligence for Barrett's esophagus: What we should and soon will do. World J Gastroenterol. 2022;28(11):1113–1122.
  15. Dmitriev K, Kaufman AE, Javed AA, et al. Classification of Pancreatic Cysts in Computed Tomography Images Using a Random Forest and Convolutional Neural Network Ensemble. Med Image Comput Comput Assist Interv. 2017;10435:150–158.
  16. Emile SH, Ghareeb W, Elfeki H, et al. Development and Validation of an Artificial Intelligence–Based Model to Predict Gastroesophageal Reflux Disease After Sleeve Gastrectomy. Obes Surg. 2022;32(8):2537–2547.
Creative Commons Attribution License

©2023 Ganipisetti. This is an open access article distributed under the terms of the, which permits unrestricted use, distribution, and build upon your work non-commercially.

Citations

Journal Menu

Useful Links