ARTIFICIAL INTELLIGENCE APPLICATION IN COLONOSCOPY SCREENING: A LITERATURE REVIEW

Kamila Mozga; Mateusz Jasiński; Marcin Narloch; Jan Tomczyk; Aleksandra Żywicka; Oskar Sienkiel; Michał Szalach

doi:10.31435/ijitss.3(47).2025.3779

Authors

Kamila Mozga Students’ Scientific Society at the 2nd Department and Clinic of General, Gastroenterological and Gastrointestinal Oncology Surgery, Medical University of Lublin, al. Racławickie 1, 20-059 Lublin, Poland https://orcid.org/0009-0000-9661-0396
Mateusz Jasiński University Clinical Hospital No. 4 in Lublin, ul. Jaczewskiego 8, 20-400 Lublin, Poland https://orcid.org/0000-0001-8218-6045
Marcin Narloch University Clinical Hospital No. 4 in Lublin, ul. Jaczewskiego 8, 20-400 Lublin, Poland https://orcid.org/0009-0005-8717-4031
Jan Tomczyk Independent Public Healthcare Institution in Puławy, ul. Józefa Bema 1, 24-100 Puławy, Poland https://orcid.org/0000-0003-1034-3819
Aleksandra Żywicka 1st Military Clinical Hospital in Lublin, al. Racławickie 23, 20-049 Lublin, Poland https://orcid.org/0000-0003-2015-830X
Oskar Sienkiel 7th Naval Hospital in Gdańsk, ul. Polanki 117, 80-305 Gdańsk, Poland https://orcid.org/0009-0002-4524-0721
Michał Szalach Independent Public Healthcare Institution in Puławy, ul. Józefa Bema 1, 24-100 Puławy, Poland https://orcid.org/0000-0001-6933-0612

DOI:

https://doi.org/10.31435/ijitss.3(47).2025.3779

Keywords:

Mass Screening, Colonoscopy, Colorectal Neoplasms, Artificial Intelligence, Machine Learning

Abstract

Background: Colorectal cancer (CRC) is the third most commonly diagnosed cancer globally and remains a leading cause of cancer-related deaths. Despite the effectiveness of colonoscopy in reducing CRC incidence and mortality through adenoma removal, some polyps are frequently missed. Artificial intelligence (AI) has recently appeared as a promising tool to enhance detection rates during colonoscopy.

Aim of the study: This study aims to compare AI-assisted colonoscopy with standard colonoscopy in terms of adenoma detection rate and polyp detection rate. The goal is to evaluate whether one approach is superior to the other.

Material and methods: A systematic literature search of the PubMed database was performed for studies published between 2015 and 2025. Search terms included “artificial intelligence”, “machine learning”, “colonoscopy”, and “mass screening”. Only English-language studies directly comparing adenoma and polyp detection rates between AI and standard colonoscopy procedures were included. A total of 18 studies involving 12,000 patients met the inclusion criteria.

Results: The AI group consistently demonstrated higher adenoma detection rates compared to the standard colonoscopy group, with 36.06% vs. 28.85%, respectively. Similarly, AI showcased greater polyp detection rates, detecting polyps in 41.05% of patients compared to 34.17% in the standard colonoscopy group. Advanced AI techniques reported the highest detection rates. AI showed enhanced performance in identifying diminutive lesions and polyps located in challenging regions. Importantly, AI did not significantly prolong withdrawal times.

Conclusions: AI integration into colonoscopy improves adenoma and polyp detection rates across diverse patient populations and clinical settings. Even among experienced endoscopists, AI provides added diagnostic value. The findings highlight AI’s potential to enhance CRC screening, though further studies are needed to standardize AI tools, validate their efficacy in real-world settings, and assess long-term clinical outcomes.

References

Sung, H., Ferlay, J., Siegel, R. L., Laversanne, M., Soerjomataram, I., Jemal, A., & Bray, F. (2021). Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA: a cancer journal for clinicians, 71(3), 209–249. https://doi.org/10.3322/caac.21660

Menon, G., & Cagir, B. (2025). Colon Cancer. In StatPearls. StatPearls Publishing.

Bray, F., Laversanne, M., Sung, H., Ferlay, J., Siegel, R. L., Soerjomataram, I., & Jemal, A. (2024). Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: a cancer journal for clinicians, 74(3), 229–263. https://doi.org/10.3322/caac.21834

Matsuda, T., Fujimoto, A., & Igarashi, Y. (2025). Colorectal Cancer: Epidemiology, Risk Factors, and Public Health Strategies. Digestion, 106(2), 91–99. https://doi.org/10.1159/000543921

Carethers, J. M., & Doubeni, C. A. (2020). Causes of Socioeconomic Disparities in Colorectal Cancer and Intervention Framework and Strategies. Gastroenterology, 158(2), 354–367. https://doi.org/10.1053/j.gastro.2019.10.029

Keum, N., & Giovannucci, E. (2019). Global burden of colorectal cancer: emerging trends, risk factors and prevention strategies. Nature reviews. Gastroenterology & hepatology, 16(12), 713–732. https://doi.org/10.1038/s41575-019-0189-8

Ionescu, V. A., Gheorghe, G., Bacalbasa, N., Chiotoroiu, A. L., & Diaconu, C. (2023). Colorectal Cancer: From Risk Factors to Oncogenesis. Medicina (Kaunas, Lithuania), 59(9), 1646. https://doi.org/10.3390/medicina59091646

Sninsky, J. A., Shore, B. M., Lupu, G. V., & Crockett, S. D. (2022). Risk Factors for Colorectal Polyps and Cancer. Gastrointestinal endoscopy clinics of North America, 32(2), 195–213. https://doi.org/10.1016/j.giec.2021.12.008

Song, M., Chan, A. T., & Sun, J. (2020). Influence of the Gut Microbiome, Diet, and Environment on Risk of Colorectal Cancer. Gastroenterology, 158(2), 322–340. https://doi.org/10.1053/j.gastro.2019.06.048

Zaffaroni, G., Mannucci, A., Koskenvuo, L., de Lacy, B., Maffioli, A., Bisseling, T., Half, E., Cavestro, G. M., Valle, L., Ryan, N., Aretz, S., Brown, K., Buttitta, F., Carneiro, F., Claber, O., Blanco-Colino, R., Collard, M., Crosbie, E., Cunha, M., Doulias, T., … Möslein, G. (2024). Updated European guidelines for clinical management of familial adenomatous polyposis (FAP), MUTYH-associated polyposis (MAP), gastric adenocarcinoma, proximal polyposis of the stomach (GAPPS) and other rare adenomatous polyposis syndromes: a joint EHTG-ESCP revision. The British journal of surgery, 111(5), znae070. https://doi.org/10.1093/bjs/znae070

Bhattacharya, P., Leslie, S. W., & McHugh, T. W. (2024). Lynch Syndrome (Hereditary Nonpolyposis Colorectal Cancer). In StatPearls. StatPearls Publishing.

Frieler, M., Moore, M., & Longacre, M. L. (2023). Primary and Secondary Prevention Interventions to Reduce Risk Factors Associated with Colorectal Cancer in High-Risk Groups: a Systematic Literature Review. Journal of cancer education : the official journal of the American Association for Cancer Education, 38(3), 738–751. https://doi.org/10.1007/s13187-023-02273-0

Hollis, R. H., & Chu, D. I. (2022). Healthcare Disparities and Colorectal Cancer. Surgical oncology clinics of North America, 31(2), 157–169. https://doi.org/10.1016/j.soc.2021.11.002

Muller, C., Ihionkhan, E., Stoffel, E. M., & Kupfer, S. S. (2021). Disparities in Early-Onset Colorectal Cancer. Cells, 10(5), 1018. https://doi.org/10.3390/cells10051018

Jacobsson, M., Wagner, V., & Kanneganti, S. (2024). Screening for Colorectal Cancer. The Surgical clinics of North America, 104(3), 595–607. https://doi.org/10.1016/j.suc.2023.11.009

Ladabaum, U., Dominitz, J. A., Kahi, C., & Schoen, R. E. (2020). Strategies for Colorectal Cancer Screening. Gastroenterology, 158(2), 418–432. https://doi.org/10.1053/j.gastro.2019.06.043

Jayasinghe, M., Prathiraja, O., Caldera, D., Jena, R., Coffie-Pierre, J. A., Silva, M. S., & Siddiqui, O. S. (2023). Colon Cancer Screening Methods: 2023 Update. Cureus, 15(4), e37509. https://doi.org/10.7759/cureus.37509

Gupta S. (2022). Screening for Colorectal Cancer. Hematology/oncology clinics of North America, 36(3), 393–414. https://doi.org/10.1016/j.hoc.2022.02.001

Lee, M. W., Pourmorady, J. S., & Laine, L. (2020). Use of Fecal Occult Blood Testing as a Diagnostic Tool for Clinical Indications: A Systematic Review and Meta-Analysis. The American journal of gastroenterology, 115(5), 662–670. https://doi.org/10.14309/ajg.0000000000000495

Juul, F. E., Cross, A. J., Schoen, R. E., Senore, C., Pinsky, P. F., Miller, E. A., Segnan, N., Wooldrage, K., Wieszczy-Szczepanik, P., Armaroli, P., Garborg, K. K., Adami, H. O., Hoff, G., Kalager, M., Bretthauer, M., Holme, Ø., & Løberg, M. (2024). Effectiveness of Colonoscopy Screening vs Sigmoidoscopy Screening in Colorectal Cancer. JAMA network open, 7(2), e240007. https://doi.org/10.1001/jamanetworkopen.2024.0007

Ramphal, W., Boeding, J. R. E., Schreinemakers, J. M. J., Gobardhan, P. D., Rutten, H. J. T., & Crolla, R. M. P. H. (2020). Colonoscopy Surveillance After Colorectal Cancer: the Optimal Interval for Follow-Up. Journal of gastrointestinal cancer, 51(2), 469–477. https://doi.org/10.1007/s12029-019-00254-5

Rex D. K. (2025). Colonoscopy Remains an Important Option for Primary Screening for Colorectal Cancer. Digestive diseases and sciences, 70(5), 1595–1605. https://doi.org/10.1007/s10620-024-08760-8

Tada, N., Tamai, N., & Sumiyama, K. (2025). Screening Colonoscopy to Reduce the Incidence and Mortality of Colorectal Cancer. Digestion, 106(2), 100–106. https://doi.org/10.1159/000542113

Ameen, S., Wong, M. C., Turner, P., & Yee, K. C. (2023). Improving colorectal cancer screening - consumer-centred technological interventions to enhance engagement and participation amongst diverse cohorts. Clinics and research in hepatology and gastroenterology, 47(1), 102064. https://doi.org/10.1016/j.clinre.2022.102064

Dougherty, M. K., Brenner, A. T., Crockett, S. D., Gupta, S., Wheeler, S. B., Coker-Schwimmer, M., Cubillos, L., Malo, T., & Reuland, D. S. (2018). Evaluation of Interventions Intended to Increase Colorectal Cancer Screening Rates in the United States: A Systematic Review and Meta-analysis. JAMA internal medicine, 178(12), 1645–1658. https://doi.org/10.1001/jamainternmed.2018.4637

Wallace, M. B., Sharma, P., Bhandari, P., East, J., Antonelli, G., Lorenzetti, R., Vieth, M., Speranza, I., Spadaccini, M., Desai, M., Lukens, F. J., Babameto, G., Batista, D., Singh, D., Palmer, W., Ramirez, F., Palmer, R., Lunsford, T., Ruff, K., Bird-Liebermann, E., … Hassan, C. (2022). Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia. Gastroenterology, 163(1), 295–304.e5. https://doi.org/10.1053/j.gastro.2022.03.007

Glissen Brown, J. R., Mansour, N. M., Wang, P., Chuchuca, M. A., Minchenberg, S. B., Chandnani, M., Liu, L., Gross, S. A., Sengupta, N., & Berzin, T. M. (2022). Deep Learning Computer-aided Polyp Detection Reduces Adenoma Miss Rate: A United States Multi-center Randomized Tandem Colonoscopy Study (CADeT-CS Trial). Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association, 20(7), 1499–1507.e4. https://doi.org/10.1016/j.cgh.2021.09.009

Gupta, S., Earles, A., Bustamante, R., Patterson, O. V., Gawron, A. J., Kaltenbach, T. R., Yassin, H., Lamm, M., Shah, S. C., Saini, S. D., Fisher, D. A., Martinez, M. E., Messer, K., Demb, J., & Liu, L. (2023). Adenoma Detection Rate and Clinical Characteristics Influence Advanced Neoplasia Risk After Colorectal Polypectomy. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association, 21(7), 1924–1936.e9. https://doi.org/10.1016/j.cgh.2022.10.003

Schottinger, J. E., Jensen, C. D., Ghai, N. R., Chubak, J., Lee, J. K., Kamineni, A., Halm, E. A., Sugg-Skinner, C., Udaltsova, N., Zhao, W. K., Ziebell, R. A., Contreras, R., Kim, E. J., Fireman, B. H., Quesenberry, C. P., & Corley, D. A. (2022). Association of Physician Adenoma Detection Rates With Postcolonoscopy Colorectal Cancer. JAMA, 327(21), 2114–2122. https://doi.org/10.1001/jama.2022.6644

Rex D. K. (2022). Adenoma Detection Rate and Colorectal Cancer Prevention by Colonoscopy. JAMA, 327(21), 2088–2089. https://doi.org/10.1001/jama.2022.3822

Park, C. H., Yang, D. H., Kim, J. W., Kim, J. H., Kim, J. H., Min, Y. W., Lee, S. H., Bae, J. H., Chung, H., Choi, K. D., Park, J. C., Lee, H., Kwak, M. S., Kim, B., Lee, H. J., Lee, H. S., Choi, M., Park, D. A., Lee, J. Y., Byeon, J. S., … Chun, H. J. (2020). Clinical Practice Guideline for Endoscopic Resection of Early Gastrointestinal Cancer. Clinical endoscopy, 53(2), 142–166. https://doi.org/10.5946/ce.2020.032

Schöler, J., Alavanja, M., de Lange, T., Yamamoto, S., Hedenström, P., & Varkey, J. (2024). Impact of AI-aided colonoscopy in clinical practice: a prospective randomised controlled trial. BMJ open gastroenterology, 11(1), e001247. https://doi.org/10.1136/bmjgast-2023-001247

Parasa S. (2024). Augmenting colonoscopy with AI: insights and future directions. The lancet. Gastroenterology & hepatology, 9(10), 896–897. https://doi.org/10.1016/S2468-1253(24)00276-0

Patterson, O. V., Forbush, T. B., Saini, S. D., Moser, S. E., & DuVall, S. L. (2015). Classifying the Indication for Colonoscopy Procedures: A Comparison of NLP Approaches in a Diverse National Healthcare System. Studies in health technology and informatics, 216, 614–618.

Yang, H. J., Cho, C. W., Jang, J., Kim, S. S., Ahn, K. S., Park, S. K., & Park, D. I. (2021). Application of deep learning to predict advanced neoplasia using big clinical data in colorectal cancer screening of asymptomatic adults. The Korean journal of internal medicine, 36(4), 845–856. https://doi.org/10.3904/kjim.2020.020

Uttam, S., Hashash, J. G., LaFace, J., Binion, D., Regueiro, M., Hartman, D. J., Brand, R. E., & Liu, Y. (2019). Three-Dimensional Nanoscale Nuclear Architecture Mapping of Rectal Biopsies Detects Colorectal Neoplasia in Patients with Inflammatory Bowel Disease. Cancer prevention research (Philadelphia, Pa.), 12(8), 527–538. https://doi.org/10.1158/1940-6207.CAPR-19-0024

Fouladi, A., Asadi, A., Sherer, E. A., & Madadi, M. (2024). Cost-effectiveness Analysis of Colorectal Cancer Screening Strategies Using Active Learning and Monte Carlo Simulation. Medical decision making : an international journal of the Society for Medical Decision Making, 44(5), 554–571. https://doi.org/10.1177/0272989X241258224

Libanio, D., Antonelli, G., Marijnissen, F., Spaander, M. C., Hassan, C., Dinis-Ribeiro, M., & Areia, M. (2024). Combined gastric and colorectal cancer endoscopic screening may be cost-effective in Europe with the implementation of artificial intelligence: an economic evaluation. European journal of gastroenterology & hepatology, 36(2), 155–161. https://doi.org/10.1097/MEG.0000000000002680

Areia, M., Mori, Y., Correale, L., Repici, A., Bretthauer, M., Sharma, P., Taveira, F., Spadaccini, M., Antonelli, G., Ebigbo, A., Kudo, S. E., Arribas, J., Barua, I., Kaminski, M. F., Messmann, H., Rex, D. K., Dinis-Ribeiro, M., & Hassan, C. (2022). Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study. The Lancet. Digital health, 4(6), e436–e444. https://doi.org/10.1016/S2589-7500(22)00042-5

Park, D. K., Kim, E. J., Im, J. P., Lim, H., Lim, Y. J., Byeon, J. S., Kim, K. O., Chung, J. W., & Kim, Y. J. (2024). A prospective multicenter randomized controlled trial on artificial intelligence assisted colonoscopy for enhanced polyp detection. Scientific reports, 14(1), 25453. https://doi.org/10.1038/s41598-024-77079-1

Thiruvengadam, N. R., Solaimani, P., Shrestha, M., Buller, S., Carson, R., Reyes-Garcia, B., Gnass, R. D., Wang, B., Albasha, N., Leonor, P., Saumoy, M., Coimbra, R., Tabuenca, A., Srikureja, W., & Serrao, S. (2024). The Efficacy of Real-time Computer-aided Detection of Colonic Neoplasia in Community Practice: A Pragmatic Randomized Controlled Trial. Clinical gastroenterology and hepatology : the official clinical practice journal of the American Gastroenterological Association, 22(11), 2221–2230.e15. https://doi.org/10.1016/j.cgh.2024.02.021

Lui, T. K., Lam, C. P., To, E. W., Ko, M. K., Tsui, V. W. M., Liu, K. S., Hui, C. K., Cheung, M. K., Mak, L. L., Hui, R. W., Wong, S. Y., Seto, W. K., & Leung, W. K. (2024). Endocuff With or Without Artificial Intelligence-Assisted Colonoscopy in Detection of Colorectal Adenoma: A Randomized Colonoscopy Trial. The American journal of gastroenterology, 119(7), 1318–1325. https://doi.org/10.14309/ajg.0000000000002684

Miyaguchi, K., Tsuzuki, Y., Hirooka, N., Matsumoto, H., Ohgo, H., Nakamoto, H., & Imaeda, H. (2024). Linked-color imaging with or without artificial intelligence for adenoma detection: a randomized trial. Endoscopy, 56(5), 376–383. https://doi.org/10.1055/a-2239-8145

Hüneburg, R., Bucksch, K., Schmeißer, F., Heling, D., Marwitz, T., Aretz, S., Kaczmarek, D. J., Kristiansen, G., Hommerding, O., Strassburg, C. P., Engel, C., & Nattermann, J. (2023). Real-time use of artificial intelligence (CADEYE) in colorectal cancer surveillance of patients with Lynch syndrome-A randomized controlled pilot trial (CADLY). United European gastroenterology journal, 11(1), 60–68. https://doi.org/10.1002/ueg2.12354

Ahmad, A., Wilson, A., Haycock, A., Humphries, A., Monahan, K., Suzuki, N., Thomas-Gibson, S., Vance, M., Bassett, P., Thiruvilangam, K., Dhillon, A., & Saunders, B. P. (2023). Evaluation of a real-time computer-aided polyp detection system during screening colonoscopy: AI-DETECT study. Endoscopy, 55(4), 313–319. https://doi.org/10.1055/a-1966-0661

Shaukat, A., Lichtenstein, D. R., Somers, S. C., Chung, D. C., Perdue, D. G., Gopal, M., Colucci, D. R., Phillips, S. A., Marka, N. A., Church, T. R., Brugge, W. R., & SKOUT™ Registration Study Team (2022). Computer-Aided Detection Improves Adenomas per Colonoscopy for Screening and Surveillance Colonoscopy: A Randomized Trial. Gastroenterology, 163(3), 732–741. https://doi.org/10.1053/j.gastro.2022.05.028

Repici, A., Spadaccini, M., Antonelli, G., Correale, L., Maselli, R., Galtieri, P. A., Pellegatta, G., Capogreco, A., Milluzzo, S. M., Lollo, G., Di Paolo, D., Badalamenti, M., Ferrara, E., Fugazza, A., Carrara, S., Anderloni, A., Rondonotti, E., Amato, A., De Gottardi, A., Spada, C., … Hassan, C. (2022). Artificial intelligence and colonoscopy experience: lessons from two randomised trials. Gut, 71(4), 757–765. https://doi.org/10.1136/gutjnl-2021-324471

Yao, L., Zhang, L., Liu, J., Zhou, W., He, C., Zhang, J., Wu, L., Wang, H., Xu, Y., Gong, D., Xu, M., Li, X., Bai, Y., Gong, R., Sharma, P., & Yu, H. (2022). Effect of an artificial intelligence-based quality improvement system on efficacy of a computer-aided detection system in colonoscopy: a four-group parallel study. Endoscopy, 54(8), 757–768. https://doi.org/10.1055/a-1706-6174

Repici, A., Badalamenti, M., Maselli, R., Correale, L., Radaelli, F., Rondonotti, E., Ferrara, E., Spadaccini, M., Alkandari, A., Fugazza, A., Anderloni, A., Galtieri, P. A., Pellegatta, G., Carrara, S., Di Leo, M., Craviotto, V., Lamonaca, L., Lorenzetti, R., Andrealli, A., Antonelli, G., … Hassan, C. (2020). Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology, 159(2), 512–520.e7. https://doi.org/10.1053/j.gastro.2020.04.062

Liu, W. N., Zhang, Y. Y., Bian, X. Q., Wang, L. J., Yang, Q., Zhang, X. D., & Huang, J. (2020). Study on detection rate of polyps and adenomas in artificial-intelligence-aided colonoscopy. Saudi journal of gastroenterology : official journal of the Saudi Gastroenterology Association, 26(1), 13–19. https://doi.org/10.4103/sjg.SJG_377_19

Wang, P., Berzin, T. M., Glissen Brown, J. R., Bharadwaj, S., Becq, A., Xiao, X., Liu, P., Li, L., Song, Y., Zhang, D., Li, Y., Xu, G., Tu, M., & Liu, X. (2019). Real-time automatic detection system increases colonoscopic polyp and adenoma detection rates: a prospective randomised controlled study. Gut, 68(10), 1813–1819. https://doi.org/10.1136/gutjnl-2018-317500

Xu, L., He, X., Zhou, J., Zhang, J., Mao, X., Ye, G., Chen, Q., Xu, F., Sang, J., Wang, J., Ding, Y., Li, Y., & Yu, C. (2021). Artificial intelligence-assisted colonoscopy: A prospective, multicenter, randomized controlled trial of polyp detection. Cancer medicine, 10(20), 7184–7193. https://doi.org/10.1002/cam4.4261

Luo, Y., Zhang, Y., Liu, M., Lai, Y., Liu, P., Wang, Z., Xing, T., Huang, Y., Li, Y., Li, A., Wang, Y., Luo, X., Liu, S., & Han, Z. (2021). Artificial Intelligence-Assisted Colonoscopy for Detection of Colon Polyps: a Prospective, Randomized Cohort Study. Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract, 25(8), 2011–2018. https://doi.org/10.1007/s11605-020-04802-4