{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,29]],"date-time":"2026-01-29T01:26:50Z","timestamp":1769650010104,"version":"3.49.0"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T00:00:00Z","timestamp":1766707200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T00:00:00Z","timestamp":1769558400000},"content-version":"vor","delay-in-days":33,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"This study was funded by Odin Medical Ltd"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["npj Digit. Med."],"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>\n                    Previously, colorectal polyp computer-aided detection (CADe) systems required on-site high-performance hardware installations (e.g., FPGAs\/GPUs), creating practical challenges to upgrades and tying hospitals to legacy hardware. Cloud-based CADe solutions overcome these constraints. Hospitals can use low-specification\/low-cost hardware to stream data to the cloud for analysis, enabling frequent AI hardware and algorithm updates. Furthermore, existing CADe systems\u2019 benefits are largely limited to smaller, less clinically relevant polyps (\u2009&lt;\u200910\u2009mm). This parallel-group RCT evaluated a real-time cloud-deployed CADe-system trained on an enhanced dataset of clinically significant polyps (large polyps(\u2009\u2265\u200910\u2009mm) and sessile-serrated-lesions(SSLs)). Patients from eight centers across four European countries (841 patients, 22 endoscopists) were randomized to standard or CADe-assisted colonoscopy. Co-primary endpoints were (1) superior Adenomas Per-Colonoscopy (APC), (2) non-inferior Positive Percent-Agreement (PPA) (proportion of resections confirmed as clinically relevant polyps). CADe improved (\n                    <jats:italic>p<\/jats:italic>\n                    \u2009&lt;\u20090.05): APC (0.82 vs. 0.62, Ratio 1.33[95% CI 1.06\u20131.67]), adenoma detection-rate (43.2% vs. 35.9%), SSL (0.08 vs. 0.03, Ratio 3.30[95% CI 1.41\u20137.57]), and large polyp (0.12 vs. 0.05, Ratio 2.36[95% CI 1.33\u20134.17]) detection. PPA was non-inferior, and average cloud-network latency was 59.4\u2009ms per minute, with 99.6% under the 100\u2009ms threshold required for real-time use. This RCT demonstrates the feasibility and efficacy of a real-time cloud-based CADe system, with promising outcomes for clinically significant polyps (large polyps and SSLs). Future research should explore optimizing CADe systems' performance. ClinicalTrials.gov (NCT05730192[15\/02\/2023]).\n                  <\/jats:p>","DOI":"10.1038\/s41746-025-02270-1","type":"journal-article","created":{"date-parts":[[2025,12,26]],"date-time":"2025-12-26T03:23:28Z","timestamp":1766719408000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A novel cloud-based artificial intelligence for real-time detection of colorectal neoplasia \u2013 a randomized controlled trial (EAGLE)"],"prefix":"10.1038","volume":"9","author":[{"given":"Rawen","family":"Kader","sequence":"first","affiliation":[]},{"given":"Cesare","family":"Hassan","sequence":"additional","affiliation":[]},{"given":"\u00c1ngel","family":"Lanas","sequence":"additional","affiliation":[]},{"given":"Marcin","family":"Roma\u0144czyk","sequence":"additional","affiliation":[]},{"given":"Tomasz","family":"Roma\u0144czyk","sequence":"additional","affiliation":[]},{"given":"Bronis\u0142aw","family":"Kotowski","sequence":"additional","affiliation":[]},{"given":"Carlos Sostres","family":"Homedes","sequence":"additional","affiliation":[]},{"given":"Benedetto","family":"Mangiavillano","sequence":"additional","affiliation":[]},{"given":"Giacomo","family":"Bonanno","sequence":"additional","affiliation":[]},{"given":"Laurence B.","family":"Lovat","sequence":"additional","affiliation":[]},{"given":"Micha\u0142","family":"Kami\u0144ski","sequence":"additional","affiliation":[]},{"given":"Siegbert","family":"Faiss","sequence":"additional","affiliation":[]},{"given":"Alessandro","family":"Repici","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,12,26]]},"reference":[{"key":"2270_CR1","first-page":"394","volume":"68","author":"F Bray","year":"2018","unstructured":"Bray, F. et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 68, 394\u2013424 (2018).","journal-title":"CA Cancer J. Clin."},{"key":"2270_CR2","doi-asserted-by":"publisher","first-page":"687","DOI":"10.1056\/NEJMoa1100370","volume":"366","author":"AG Zauber","year":"2012","unstructured":"Zauber, A. G., van Ballegooijen, M. & Schapiro, M. Colonoscopic polypectomy and long-term prevention of colorectal-cancer deaths. N. Engl. J. Med. 366, 687\u2013696 (2012).","journal-title":"N. Engl. J. Med."},{"key":"2270_CR3","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1016\/j.cgh.2024.07.039","volume":"23","author":"R Kader","year":"2024","unstructured":"Kader, R. et al. Systematic review and meta-analysis: the three-year post-colonoscopy colorectal cancer rate as per the World Endoscopy Organization methodology. Clin. Gastroenterol. Hepatol. 23, 519\u2013530 (2024).","journal-title":"Clin. Gastroenterol. Hepatol."},{"key":"2270_CR4","doi-asserted-by":"publisher","first-page":"1661","DOI":"10.1053\/j.gastro.2019.01.260","volume":"156","author":"S Zhao","year":"2019","unstructured":"Zhao, S. et al. Magnitude, risk factors, and factors associated with adenoma miss rate of tandem colonoscopy: a systematic review and meta-analysis. Gastroenterology 156, 1661\u20131674.e11 (2019).","journal-title":"Gastroenterology"},{"key":"2270_CR5","doi-asserted-by":"publisher","first-page":"787","DOI":"10.1016\/j.gie.2023.11.014","volume":"99","author":"JC Anderson","year":"2024","unstructured":"Anderson, J. C. et al. Endoscopist adenomas-per-colonoscopy detection rates and risk for postcolonoscopy colorectal cancer: data from the New Hampshire Colonoscopy Registry. Gastrointest. Endosc. 99, 787\u2013795 (2024).","journal-title":"Gastrointest. Endosc."},{"key":"2270_CR6","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1016\/j.gie.2022.03.001","volume":"96","author":"JC Anderson","year":"2022","unstructured":"Anderson, J. C. et al. Clinically significant serrated polyp detection rates and risk for postcolonoscopy colorectal cancer: data from the New Hampshire Colonoscopy Registry. Gastrointest. Endosc. 96, 310\u2013317 (2022).","journal-title":"Gastrointest. Endosc."},{"key":"2270_CR7","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1016\/S2468-1253(22)00090-5","volume":"7","author":"DEFWM van Toledo","year":"2022","unstructured":"van Toledo, D. E. F. W. M. et al. Serrated polyp detection and risk of interval post-colonoscopy colorectal cancer: a population-based study. Lancet Gastroenterol. Hepatol. 7, 747\u2013754 (2022).","journal-title":"Lancet Gastroenterol. Hepatol."},{"key":"2270_CR8","doi-asserted-by":"publisher","first-page":"768","DOI":"10.1111\/jgh.16127","volume":"38","author":"OF Ahmad","year":"2023","unstructured":"Ahmad, O. F. et al. Identifying key mechanisms leading to visual recognition errors for missed colorectal polyps using eye-tracking technology. J. Gastroenterol. Hepatol. 38, 768\u2013774 (2023).","journal-title":"J. Gastroenterol. Hepatol."},{"key":"2270_CR9","doi-asserted-by":"publisher","first-page":"1209","DOI":"10.7326\/M22-3678","volume":"176","author":"C Hassan","year":"2023","unstructured":"Hassan, C. et al. Real-time computer-aided detection of colorectal neoplasia during colonoscopy: a systematic review and meta-analysis. Ann. Intern. Med. 176, 1209\u20131220 (2023).","journal-title":"Ann. Intern. Med."},{"key":"2270_CR10","doi-asserted-by":"publisher","first-page":"196","DOI":"10.1038\/ajg.2017.439","volume":"113","author":"KO Turner","year":"2018","unstructured":"Turner, K. O., Genta, R. M. & Sonnenberg, A. Lesions of all types exist in colon polyps of all sizes. Am. J. Gastroenterol. 113, 196\u2013201 (2018).","journal-title":"Am. J. Gastroenterol."},{"key":"2270_CR11","doi-asserted-by":"publisher","first-page":"1181","DOI":"10.1136\/gutjnl-2017-314005","volume":"66","author":"JE East","year":"2017","unstructured":"East, J. E. et al. British Society of Gastroenterology position statement on serrated polyps in the colon and rectum. Gut 66, 1181\u20131196 (2017).","journal-title":"Gut"},{"key":"2270_CR12","doi-asserted-by":"publisher","first-page":"879","DOI":"10.1016\/j.gie.2024.09.044","volume":"101","author":"E Dekker","year":"2025","unstructured":"Dekker, E. Top tips for finding and treating serrated colon lesions (with video). Gastrointest. Endosc. 101, 879\u2013884 (2025).","journal-title":"Gastrointest. Endosc."},{"key":"2270_CR13","doi-asserted-by":"publisher","first-page":"1095","DOI":"10.1056\/NEJMoa1301969","volume":"369","author":"R Nishihara","year":"2013","unstructured":"Nishihara, R. et al. Long-term colorectal-cancer incidence and mortality after lower endoscopy. N. Engl. J. Med. 369, 1095\u20131105 (2013).","journal-title":"N. Engl. J. Med."},{"key":"2270_CR14","doi-asserted-by":"publisher","first-page":"5908","DOI":"10.3748\/wjg.v27.i35.5908","volume":"27","author":"R Kader","year":"2021","unstructured":"Kader, R., Hadjinicolaou, A. V., Georgiades, F., Stoyanov, D. & Lovat, L. B. Optical diagnosis of colorectal polyps using convolutional neural networks. World J. Gastroenterol. 27, 5908\u20135918 (2021).","journal-title":"World J. Gastroenterol."},{"key":"2270_CR15","doi-asserted-by":"publisher","first-page":"368","DOI":"10.1007\/s10278-024-01200-z","volume":"38","author":"N Chatterjee","year":"2024","unstructured":"Chatterjee, N. et al. A cloud-based system for automated AI image analysis and reporting. J. Imaging Inform. Med. 38, 368\u2013379 (2024).","journal-title":"J. Imaging Inform. Med."},{"key":"2270_CR16","doi-asserted-by":"publisher","first-page":"100228","DOI":"10.1016\/j.xops.2022.100228","volume":"3","author":"JI Lim","year":"2023","unstructured":"Lim, J. I. et al. Artificial intelligence detection of diabetic retinopathy: subgroup comparison of the EyeArt system with ophthalmologists\u2019 dilated examinations. Ophthalmol. Sci. 3, 100228 (2023).","journal-title":"Ophthalmol. Sci."},{"key":"2270_CR17","first-page":"1","volume":"1","author":"G Lip","year":"2024","unstructured":"Lip, G., Novak, A., Goyen, M., Boylan, K. & Kumar, A. Adoption, orchestration, and deployment of artificial intelligence within the National Health Service\u2014facilitators and barriers: an expert roundtable discussion. BJR Artif. Intell. 1, 1\u20139 (2024).","journal-title":"BJR Artif. Intell."},{"key":"2270_CR18","doi-asserted-by":"publisher","first-page":"646","DOI":"10.1016\/j.gie.2022.11.020","volume":"97","author":"M Hussein","year":"2023","unstructured":"Hussein, M. et al. Computer-aided characterization of early cancer in Barrett\u2019s esophagus on i-scan magnification imaging: a multicenter international study. Gastrointest. Endosc. 97, 646\u2013654 (2023).","journal-title":"Gastrointest. Endosc."},{"key":"2270_CR19","doi-asserted-by":"publisher","first-page":"2629","DOI":"10.1364\/BOE.485069","volume":"14","author":"T De Carvalho","year":"2023","unstructured":"De Carvalho, T. et al. Automated colonoscopy withdrawal phase duration estimation using cecum detection and surgical tasks classification. Biomed. Opt. Express 14, 2629\u20132644 (2023).","journal-title":"Biomed. Opt. Express"},{"key":"2270_CR20","doi-asserted-by":"publisher","first-page":"404","DOI":"10.3390\/bioengineering10040404","volume":"10","author":"A Cherubini","year":"2023","unstructured":"Cherubini, A. & Dinh, N. N. A review of the technology, training, and assessment methods for the first real-time AI-enhanced medical device for endoscopy. Bioengineering 10, 404 (2023).","journal-title":"Bioengineering"},{"key":"2270_CR21","doi-asserted-by":"publisher","first-page":"303","DOI":"10.7326\/M22-1008","volume":"176","author":"M Zorzi","year":"2023","unstructured":"Zorzi, M. et al. Adenoma detection rate and colorectal cancer risk in fecal immunochemical test screening programs. Ann. Intern. Med. 176, 303\u2013310 (2023).","journal-title":"Ann. Intern. Med."},{"key":"2270_CR22","doi-asserted-by":"publisher","first-page":"1298","DOI":"10.1056\/NEJMoa1309086","volume":"370","author":"DA Corley","year":"2014","unstructured":"Corley, D. A. et al. Adenoma detection rate and risk of colorectal cancer and death. N. Engl. J. Med. 370, 1298\u20131306 (2014).","journal-title":"N. Engl. J. Med."},{"key":"2270_CR23","doi-asserted-by":"publisher","first-page":"400","DOI":"10.1001\/jama.2024.22975","volume":"333","author":"ND Pilonis","year":"2025","unstructured":"Pilonis, N. D. et al. Adenoma detection rates by physicians and subsequent colorectal cancer risk. JAMA 333, 400\u2013407 (2025).","journal-title":"JAMA"},{"key":"2270_CR24","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/j.cgh.2022.03.023","volume":"21","author":"P Wieszczy","year":"2023","unstructured":"Wieszczy, P. et al. Comparison of quality measures for detection of neoplasia at screening colonoscopy. Clin. Gastroenterol. Hepatol. 21, 200\u2013209.e6 (2023).","journal-title":"Clin. Gastroenterol. Hepatol."},{"key":"2270_CR25","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1016\/j.gie.2014.07.058","volume":"81","author":"DK Rex","year":"2015","unstructured":"Rex, D. K. et al. Quality indicators for colonoscopy. Gastrointest. Endosc. 81, 31\u201353 (2015).","journal-title":"Gastrointest. Endosc."},{"key":"2270_CR26","doi-asserted-by":"publisher","first-page":"881","DOI":"10.1136\/gutjnl-2024-334456","volume":"74","author":"DK Rex","year":"2025","unstructured":"Rex, D. K. et al. Detection of large flat colorectal lesions by artificial intelligence: a persistent weakness and blind spot. Gut 74, 881\u2013883 (2025).","journal-title":"Gut"},{"key":"2270_CR27","doi-asserted-by":"publisher","first-page":"1102","DOI":"10.3390\/diagnostics13061102","volume":"13","author":"M Spadaccini","year":"2023","unstructured":"Spadaccini, M. et al. Artificial intelligence-aided endoscopy and colorectal cancer screening. Diagnostics 13, 1102 (2023).","journal-title":"Diagnostics"},{"key":"2270_CR28","doi-asserted-by":"publisher","first-page":"911","DOI":"10.1016\/S2468-1253(24)00161-4","volume":"9","author":"A Seager","year":"2024","unstructured":"Seager, A. et al. Polyp detection with colonoscopy assisted by the GI Genius artificial intelligence endoscopy module compared with standard colonoscopy in routine colonoscopy practice (COLO-DETECT): a multicentre, open-label, parallel-arm, pragmatic randomised controlled trial. Lancet Gastroenterol. Hepatol. 9, 911\u2013923 (2024).","journal-title":"Lancet Gastroenterol. Hepatol."},{"key":"2270_CR29","doi-asserted-by":"publisher","first-page":"512","DOI":"10.1053\/j.gastro.2020.04.062","volume":"159","author":"A Repici","year":"2020","unstructured":"Repici, A. et al. Efficacy of real-time computer-aided detection of colorectal neoplasia in a randomized trial. Gastroenterology 159, 512\u2013520.e7 (2020).","journal-title":"Gastroenterology"},{"key":"2270_CR30","doi-asserted-by":"publisher","first-page":"423","DOI":"10.1136\/flgastro-2021-101994","volume":"13","author":"R Kader","year":"2022","unstructured":"Kader, R. et al. Survey on the perceptions of UK gastroenterologists and endoscopists to artificial intelligence. Frontline Gastroenterol 13, 423\u2013429 (2022).","journal-title":"Frontline Gastroenterol"},{"key":"2270_CR31","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1053\/j.gastro.2020.03.025","volume":"159","author":"RGS Meester","year":"2020","unstructured":"Meester, R. G. S., van Herk, M. M. A. G. C., Lansdorp-Vogelaar, I. & Ladabaum, U. Prevalence and clinical features of sessile serrated polyps: a systematic review. Gastroenterology 159, 105\u2013118.e25 (2020).","journal-title":"Gastroenterology"},{"key":"2270_CR32","unstructured":"U.S. Food and Drug Administration. De Novo Classification Request for GI Genius (DEN200055): De Novo Summary. https:\/\/www.accessdata.fda.gov\/cdrh_docs\/reviews\/DEN200055.pdf (2021)."},{"key":"2270_CR33","doi-asserted-by":"publisher","first-page":"1364","DOI":"10.1038\/s41591-020-1034-x","volume":"26","author":"X Liu","year":"2020","unstructured":"Liu, X. et al. Reporting guidelines for clinical trial reports for interventions involving artificial intelligence: the CONSORT-AI extension. Nat. Med. 26, 1364\u20131374 (2020).","journal-title":"Nat. Med."},{"key":"2270_CR34","doi-asserted-by":"publisher","first-page":"732","DOI":"10.1053\/j.gastro.2022.05.028","volume":"163","author":"A Shaukat","year":"2022","unstructured":"Shaukat, A. et al. Computer-aided detection improves adenomas per colonoscopy for screening and surveillance colonoscopy: a randomized trial. Gastroenterology 163, 732\u2013741 (2022).","journal-title":"Gastroenterology"},{"key":"2270_CR35","unstructured":"U.S. Food and Drug Administration. SKOUTTM System (510(k) No. K213686) \u2014 Summary of Safety & Effectiveness. https:\/\/www.accessdata.fda.gov\/cdrh_docs\/pdf21\/K213686.pdf (2022)."}],"container-title":["npj Digital Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02270-1","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02270-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02270-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T12:14:53Z","timestamp":1769602493000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s41746-025-02270-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,26]]},"references-count":35,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,12]]}},"alternative-id":["2270"],"URL":"https:\/\/doi.org\/10.1038\/s41746-025-02270-1","relation":{},"ISSN":["2398-6352"],"issn-type":[{"value":"2398-6352","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,26]]},"assertion":[{"value":"11 May 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"26 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"R.K., L.B.L., C.H., A.R., and M.R. have received medical consultancy fees from Odin Medical Ltd. M.R. has received medical consultancy fees from Olympus. M.R. and T.R. have received medical consultancy fees from Medtronic. A.R., C.H., and M.R. competing interests postdate the study. The remaining co-authors (A.L., B.K., C.S.H., B.M., G.B., M.K., and S.F.) declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"84"}}