Authors :
Vanaja. R.
Volume/Issue :
Volume 10 - 2025, Issue 11 - November
Google Scholar :
https://tinyurl.com/5afbfuzj
Scribd :
https://tinyurl.com/24wytk65
DOI :
https://doi.org/10.38124/ijisrt/25nov452
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Abstract :
Capsule endoscopy is a noninvasive diagnostic tool that allows direct visualization of the gastrointestinal (GI) tract
using a swallowable, camera-equipped capsule [1]. It has revolutionized the evaluation of small bowel diseases such as obscure
gastrointestinal bleeding, Crohn’s disease, celiac disease, and small bowel tumors [4]. With the integration of Artificial
Intelligence (AI), the diagnostic process has become faster, more accurate, and less dependent on manual image review. Nurses
play a vital role in patient preparation, procedure monitoring, and post-procedure data management. Their training and active
participation ensure patient safety, comfort, and efficiency throughout the process. This paper discusses the principles of capsule
endoscopy, the integration of AI in diagnostic interpretation, and the evolving responsibilities and competencies required for
nurses in this advanced clinical setting.
References :
- Beg, S., Card, T., Sidhu, R., & Ragunath, K. (2021). The role of nurses in capsule endoscopy services. *Gastrointestinal Nursing, 19*(5), 36–43.
- Enns, R. A., Hookey, L., Armstrong, D., & Leontiadis, G. I. (2017). Clinical practice guidelines for the use of video capsule endoscopy. *Canadian Journal of Gastroenterology and Hepatology*, 2017, 1–9.
- Iddan, G. J., Meron, G., Glukhovsky, A., & Swain, P. (2000). Wireless capsule endoscopy. *Nature*, 405(6785), 417.
- Klang, E., Barash, Y., Margalit, R. Y., et al. (2020). Deep learning in capsule endoscopy: Automated detection of small bowel mucosal abnormalities. *Gastrointestinal Endoscopy, 91*(3), 606–613.
- Koulaouzidis, A., Douglas, S., & Plevris, J. N. (2015). Capsule endoscopy and the expanding role of nurses. *World Journal of Gastroenterology, 21*(2), 529–540.
Liao, Z., Gao, R., Xu, C., & Li, Z. S. (2010). Indications and detection, completion, and retention rates of small-bowel capsule endoscopy: A systematic review. *Gastrointestinal Endoscopy, 71*(2), 280–286.
- Pasha, S. F., Leighton, J. A., Das, A., et al. (2020). Comparison of capsule endoscopy and colonoscopy for small bowel evaluation. *American Journal of Gastroenterology, 115*(4), 623–631.
- Pennazio, M., Rondonotti, E., & de Franchis, R. (2015). Capsule endoscopy in clinical practice: 2005–2015. *Annals of Gastroenterology, 28*(1), 17–25.
- Rondonotti, E., Pennazio, M., & Toth, E. (2018). Small bowel capsule endoscopy: Current status and future directions. *Nature Reviews Gastroenterology & Hepatology, 15*(6), 347–359.
- Tai, F. W. D., Parker, C., Sidhu, R., McAlindon, M., Davison, C., Smith, G. V., & Panter, S. (2022). Training pathway for small bowel capsule endoscopy in the UK. Frontline Gastroenterology, 13(3), 218–223. https://doi.org/10.1136/flgastro-2021-102047
- Zou, W. Y., Cao, J., & Hu, X. (2022). Artificial intelligence in capsule endoscopy: A review. *Frontiers in Medicine, 9*, 870126.
Capsule endoscopy is a noninvasive diagnostic tool that allows direct visualization of the gastrointestinal (GI) tract
using a swallowable, camera-equipped capsule [1]. It has revolutionized the evaluation of small bowel diseases such as obscure
gastrointestinal bleeding, Crohn’s disease, celiac disease, and small bowel tumors [4]. With the integration of Artificial
Intelligence (AI), the diagnostic process has become faster, more accurate, and less dependent on manual image review. Nurses
play a vital role in patient preparation, procedure monitoring, and post-procedure data management. Their training and active
participation ensure patient safety, comfort, and efficiency throughout the process. This paper discusses the principles of capsule
endoscopy, the integration of AI in diagnostic interpretation, and the evolving responsibilities and competencies required for
nurses in this advanced clinical setting.