No Image Available

Gastrointestinal artificial intelligence

GI Genius™ intelligent endoscopy module

<p>The GI Genius™ intelligent endoscopy module is the first-to-market, computer-aided polyp detection system powered by artificial intelligence.</p>

Contact a representative

Features


ColonPRO™ software

Unlock the potential of AI in colonoscopy. Explore what's new:

Barrx™ flex RFA energy generator

Focus on what matters

Detection with improved performance

Robust polyp detection experience with ColonPRO™ software.25

 

With the launch of the 4th software upgrade for the GI Genius™ module—ColonPRO™ software—we continue to uphold our commitment to innovation by elevating AI-enabled polyp detection. 

 

Proven technology with meaningful impact

The GI Genius™ module is your ever-vigilant second observer - designed to help you organize results and enhance patient care.

The GI Genius™ has been proven to help improve care across both experienced and inexperienced endoscopists in academic and community settings:

  • 50% reduction in adenoma and polyp miss rate5
  • 4.2% increase in sessile detection rate13
  • 14% increase in adenoma detection rate3

 

 

Barrx™ 360 express RFA balloon catheter

Diagnose with confidence

Optical diagnosis empowered by CADx

Imagine the ability to reduce the variability of colorectal polyp size estimation with AI-assisted support.

 

GI Genius™ ColonPRO™ software could unlock the ability to provide a measurement of colon polyp size to offer objective estimation.

 

AI support could help your clinical decisions to make therapeutic choices during real-time workflows:

  • 87% sizing accuracy53
  • 100% AI solution - no additional hardware required*52
PillCam™ SB 3 sensor belt

Size the risks

Measure the impact

With GI Genius™ by your side, you can apply cost-saving strategies with confidence.

 

The clinical performance of GI Genius™ CADx module was assessed in a prospective study  that demonstrated its effectiveness in meeting the international thresholds for adopting leave in situ strategies:

  • 97.6% CADx Negative predictive value23
  • >95% Agreement on surveillance interval23
PillCam™ SB 3 sensor belt

Measure quality

Get AI-enabled quality metrics

Optimize your colonoscopy practice with ColonPRO™ procedure highlights.

 

The new GI Genius™ system includes the ability to capture highlights from your colonoscopy to better document important quality metrics. 

 

Procedure highlights include:

  • Procedure duration
  • Withdrawal time
  • Effective inspection time: time spent inspecting the mucosa
  • Bowel Cleanliness: per-segment and overall BBPS Score
  • Anatomical Landmarks: detection of ileocecal valve and appendiceal foramen

 

We are looking ahead to enable better documentation with richer insights into your colonoscopy procedures


GI Genius™ model 300

It’s not the part you think about – but it’s the part  that powers the ColonPRO™ software. 

The Next generation CE cleared hardware is designed to be: 

Powerful

Designed to easily scale and host multiple AI applications for real-time results. 

  • Strong computation power with NVIDIA IGX GPU to enable multiple AI software applications.
  • Low latency to enable high performance real-time AI software applications. 

Versatile

Built to integrate into your existing workflow

  • Compatible with all major endoscopic equipment brands
  • Supports 4K resolution
  • Allows the integration of third-party AI applications

Secure

Keep patient information protected with responsible AI practices

  • Compliant with data privacy regulations
  • Does not store patient information
  • Closed AI algorithm and software applications that do not perform real-time reinforcement learning.


AI Access™ platform

Smarter AI. Smarter insights. Seamless integration.

Grab hold of the future today

AI is here, and so are the possibilities for healthcare.

The GI Genius™ module now enables AI Access™ Platform.

AI Access is a digital ecosystem that will allow third party developers to host responsible, regulated AI applications through the GI Genius™ module.  

Our vision is to help standarize care with a suite of AI solutions so physicians can access what they need for the right patient at the right time.

Related links

Capsule Endoscopy System Tech Support Promo Box

Technical support

Get technical support for all endoscopy products.

Email us
Phone UK & IE: +44 1923 201860

  1. Hunt, A. U.S. Food & Drug Administration. FDA authorizes marketing of first device that uses artificial intelligence to help detect potential signs of colon cancer. April 09, 2021. Accessed Jan 3, 2022.
  2. Spadaccini, M., et al., Combination of Mucosa-Exposure Device and Computer-Aided Detection for Adenoma Detection During Colonoscopy: A Randomized Trial.Gastroenterology, 2023.​
  3. Repici, A., et al., Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial. Gastroenterology, 2020. 159(2):p. 512-520 e7.​
  4. Repici, A., et al., Artificial intelligence and colonoscopy experience: lessons from two randomised trials. Gut, 2022. 71(4): p. 757-765.​
  5. Wallace, M.B., et al., Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia. Gastroenterology, 2022. 163(1): p. 295-304 e5.​
  6. Karsenti, D., et al., Effect of real-time computer-aided detection of colorectal adenoma in routine colonoscopy (COLO-GENIUS): a single-centre randomised controlled trial. Lancet Gastroenterol Hepatol, 2023.​
  7. Ahmad, A., et al., Evaluation of a real-time computer-aided polyp detection system during screening colonoscopy: AI-DETECT study. Endoscopy, 2023. 55(4): p.313-319.​
  8. Mangas-Sanjuan C. et al. Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias. https://doi.org/10.7326/M22-2619​
  9. Engelke, et al. Prospective study of computer-aided detection of colorectal adenomas in hospitalized patients https://doi.org/10.1080/00365521.2023.2212309.​
  10. Seager, A. et al. (2024). 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, parallelarm, pragmatic randomised controlled trial. The Lancet Gastroenterology & Hepatology, 9(10), 911-923.​
  11. Thiruvengadam, N. R. et al. (2024). The efficacy of real-time computer-aided detection of colonic neoplasia in community practice: A pragmatic randomized controlled trial. Clinical Gastroenterology and Hepatology​
  12. Biffi, C., Antonelli, G., Bernhofer, S., Hassan, C., Hirata, D., Iwatate, M., Maieron, A., Salvagnini, P., Cherubini, A., 2024. REAL-Colon: A dataset for developing real-world AI applications in colonoscopy. ​
  13. Keswani, R.N., Thakkar, U., Sals, A., Pandolfino, J.E., 2023. A Computer-Aided Detection (CADe) System Significantly Improves Polyp Detection in Routine Practice. ​
  14. Cherubini A., Ngo Dinh, N. 2023. A Review of the Technology, Training, and Assessment Methods for the First Real-Time AI-Enhanced Medical Device for Endoscopy. Bioengineering. 10(4) 404. ​
  15. Troya, J., Sudarevic, B., Krenzer, A., Banck, M., Brand, M., Walter, B.M., Puppe, F., Zoller, W.G., Meining, A., Hann, A., 2023. Direct comparison of multiple computer-aided polyp detection systems. ​
  16. Cherubini, A. and East, J.E. 2023 Gorilla in the room: Even experts can miss polyps at colonoscopy and how AI helps complex visual perception tasks. ​
  17. Barkun, A.N., von Renteln, D., Sadri, H. 2023 Cost-effectiveness of Artificial Intelligence-Aided Colonoscopy for Adenoma Detection in Colon Cancer Screening. ​
  18. Di Napoli, G., Lee, L. S., 2023 The brave new world of artificial intelligence: dawn of a new era. ​
  19. Hassan, C., Povero, M., Pradelli, L., Spadaccini, M., Repici, A., 2023 Cost-utility analysis of real-time artificial intelligent-assisted colonoscopy in Italy. ​
  20. Tham, S., Koh, F.H., Teo, E.K., Lin, C.L., Foo, F.J., 2023 Knowledge, perceptions and behaviours of endoscopists towards the use of artificial intelligence-aided colonoscopy. ​
  21. Thiruvengadam, N.R., Cote, G., Gupta, S., Rodrigues, M., Schneider, Y., Arain, M.A., Solaimani, P., Serrao, S., Kochman, M.L., Saumoy, M., 2023. An Evaluation of Critical Factors for the Cost-Effectiveness of Real-Time Computer-Aided Detection: Sensitivity and Threshold Analyses Using a Microsimulation Model. ​
  22. Biffi, C., Salvagnini, P., Dinh, N.N., Hassan, C., Sharma, P., GI Genius CADx Study Group, Cherubini, A., 2022. A novel AI device for real-time optical characterization of colorectal polyps. ​
  23. Hassan, C., Balsamo, G., Lorenzetti, R., Zullo, A., Antonelli, G., 2022 Artificial Intelligence Allows Leaving-In-Situ Colorectal Polyps. Clin. Gastroenterol. Hepatol. Off. Clin. Pract. J. Am. Gastroenterol. ​
  24. Reverberi, C., Rigon, T., Solari, A., Hassan, C., Cherubini, P., GI Genius CADx Study Group, Cherubini, A., 2022 Experimental evidence of effective human-AI collaboration in medical decision-making. ​
  25. Rex, D.K., Mori, Y., Sharma, P., Lahr, R.E., Vemulapalli, K.C., Hassan, C., 2022 Strengths and Weaknesses of an Artificial Intelligence Polyp Detection Program as Assessed by a High-Detecting Endoscopist. ​
  26. Levy, I., Bruckmayer, L., Klang, E., Ben-Horin, S., Kopylov, U., 2022 Artificial Intelligence-Aided Colonoscopy Does Not Increase Adenoma Detection Rate in Routine Clinical Practice. ​
  27. Ladabaum, U., Shepard, J., Weng, Y., Desai, M., Singer, S.J., Mannalithara, A., 2022 Computer-aided Detection of Polyps Does Not Improve Colonoscopist Performance in a Pragmatic Implementation Trial. ​
  28. ​Chin, S.E., Wan, F.T., Ladlad, J., Chue, K.M., SKH, E.C., Teo, E.K., Lin, C.L., Foo, F.J., Koh, F.H., 2022. One-year review of real-time artificial intelligence (AI)-aided endoscopy performance. ​
  29. Koh, F.H., Ladlad, J., SKH Endoscopy Centre, Foo, F.-J., Tan, W.J., Sivarajah, S.S., Ho, L.M.L., Ng, J.-L., Koh, F.H., Chong, C., Aw, D., Kam, J.-H., Tan, A.Y.H., Tan, C.-C., Yeung, B.P.M., Wong, W.-K., Toh, B.-C., Ladlad, J., Barco, J., Chue, K.-M., Leong, F., Kong, C., Lin, C.-L., Teo, E.-K., Ng, Y.-K., Tey, T.-T., De-Roza, M.A., Lum, J., Li, X., Li, J., Mohd-Nor, N.B., Ng, S.-P., Teo, E.-K., Lin, C.-L., Foo, F.-J., 2022. Real-time artificial intelligence (AI)-aided endoscopy improves adenoma detection rates even in experienced endoscopists: a cohort study in Singapore. ​
  30. Spadaccini, M., Marco, A.D., Franchellucci, G., Sharma, P., Hassan, C., Repici, A., 2022. Discovering the first US FDA-approved computer-aided polyp detection system. ​
  31. Hassan, C., Badalamenti, M., Maselli, R., Correale, L., Iannone, A., 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., Wallace, M., Sharma, P., Rösch, T., Repici, A., 2020. Computer-aided detection-assisted colonoscopy: classification and relevance of false positives. ​
  32. Hassan, C., Wallace, M.B., Sharma, P., Maselli, R., Craviotto, V., Spadaccini, M., Repici, A., 2020. New artificial intelligence system: first validation study versus experienced endoscopists for colorectal polyp detection. ​
  33. Ortiz, Oswaldo Carballal, Sabela et al. The Lancet Gastroenterology & Hepatology, Volume 9, Issue 9, 802 – 810. An artificial intelligence-assisted system versus white light endoscopy alone for adenoma detection in individuals with Lynch syndrome (TIMELY): an international, multicentre, randomised controlled trial. ​
  34. Rondonotti et Al. Endoscopy 2024; 12(05): E676-E683 DOI: 10.1055/a-2303-0922. White light computer-aided optical diagnosis of diminutive colorectal polyps in routine clinical practice. ​
  35. Bernhofer S, Prosenz J, Duller C, Venturi D, Maieron A. Am J Gastroenterol. 2025 May 28. doi: 10.14309/ajg.0000000000003558. The Augmented Colonoscopy with Computer-Aided polyp Characterization (AC-CADx) study - prospective study comparing the diagnostic reliability of optical diagnosis of trainees with experts without AI. ​
  36. Kim JH, Wang J, Pence C, Magahis P, Dawod E, Schnoll-Sussman F, Sharaiha RZ, Wan D. Clin Endosc. 2025 May;58(3):438-447. doi: 10.5946/ce.2024.271. GI Genius increases small and right-sided adenoma and sessile serrated lesion detection rate when used with EndoCuff in a real-world setting: a retrospective United States study. ​
  37. Lagström RMB, Bräuner KB, Bielik J, Rosen AW, Crone JG, Gögenur I, Bulut M. Endosc Int Open. 2025 Feb 26;13:a25215169. doi: 10.1055/a-2521-5169. PMID: 40018072; PMCID: PMC118660. Improvement in adenoma detection rate by artificial intelligence-assisted colonoscopy: Multicenter quasi-randomized controlled trial. ​
  38. Khouri A, Dickson C, Green A, Hanjar A, Sonnier W. JGH Open. 2024 Sep 9;8(9):e70018. doi: 10.1002/jgh3.70018. PMID: 39253018; PMCID: PMC11382257. Effect of computer aided detection device on the adenoma detection rate and serrated detection rate among trainee fellows. ​
  39. ​Chow KW, Bell MT, Cumpian N, Amour M, Hsu RH, Eysselein VE, Srivastava N, Fleischman MW, Reicher S. World J Gastrointest Endosc. 2024 Jun 16;16(6):335-342. doi: 10.4253/wjge.v16.i6.335. PMID: 38946853; PMCID: PMC11212514. Long-term impact of artificial intelligence on colorectal adenoma detection in high-risk colonoscopy. ​
  40. Schöler J, Alavanja M, de Lange T, Yamamoto S, Hedenström P, Varkey J. Impact of AI-aided colonoscopy in clinical practice: a prospective randomised controlled trial. BMJ Open Gastroenterol. 2024 Jan 30;11(1):e001247. doi: 10.1136/bmjgast-2023-001247. PMID: 38290758; PMCID: PMC10870789.​
  41. Rønborg SN, Ujjal S, Kroijer R, Ploug M. Assessing the potential of artificial intelligence to enhance colonoscopy adenoma detection in clinical practice: a prospective observational trial. Clin Endosc. 2024 Nov;57(6):783-789. doi: 10.5946/ce.2024.038. Epub 2024 Aug 23. PMID: 39188117; PMCID: PMC11637665.​
  42. Ahsan M, Anderson Z, Jarbath M, Bakr M, Phillips RW. The Impact of Computer-aided Detection Technology in Adenoma Detection Rate Among Experienced Endoscopists in the Community Setting. J Community Hosp Intern Med Perspect. 2024 Sep 9;14(5):42-48. doi: 10.55729/2000-9666.1396. PMID: 39399190; PMCID: PMC11466340.​
  43. Koh GE, Ng B, Lagström RMB, Foo FJ, Chin SE, Wan FT, Kam JH, Yeung B, Kwan C, Hassan C, Gögenur I, Koh FH. Real-World Assessment of the Efficacy of Computer-Assisted Diagnosis in Colonoscopy: A Single Institution Cohort Study in Singapore. Mayo Clin Proc Digit Health. 2024 Oct 26;2(4):647-655. doi: 10.1016/j.mcpdig.2024.10.002. PMID: 40206538; PMCID: PMC11976013.​
  44. Medtronic Launches the 1st AI System for Colonoscopy at United European Gastroenterology Week 2019. The GI Genius Intelligent Endoscopy Module Transforms Colorectal Cancer Detection Benefitting Patients and Gastroenterologists.Published: Oct17, 2019. DUBLIN and BARCELONA, Spain, Oct. 17, 2019 (GLOBE NEWSWIRE) --Medtronic plc(NYSE:MDT) (REF-17593)​
  45. 1st US FDA Authorizes Marketing of First Device that Uses Artificial Intelligence to Help Detect Pot(VV-00158)​
  46. Medtronic wins U.S. Department of Veterans Affairs contract to provide GI Geniusintelligentendoscopymodulefor artificialintelligence (AI) assistedcolon cancer screening. Medtronic. https://news.medtronic.com/Medtronic-wins-U-S-Department-of-Veterans-Affairs-contract-to-provide-GI-Genius-TM-intelligentendos copy-module-for-artificial-intelligence-AI-assisted-colon-cancer-screening. Published Oct 5, 2022. Accessed April 2, 2024. (REF-23991)​
  47. GI Genius named to Fortune 2022 ‘Change the World’ list Medtronic. https://news.medtronic.com/GI-Genius-TM-named-to-FORTUNE-2022-Change-the-World-list/ . Published Oct 10, 2022. Accessed April 2, 2024.(REF-30086)​
  48. Medtronic expands Health Equity Assistance Program for colon cancer screening with support from Amazon Web Services; Completes first installation of donated GI Geniusintelligent endoscopy modules. Medtronic. https://news.medtronic.com/2022-07-15-Medtronic-expands-Health-Equity-Assistance-Program-for-colon-cancer-screening-with-support-from-Amazon-Web-Services-Completes-first-installation-of-donated-GI-Genius-TM-intelligent-endoscopymodules Published July 15, 2022. Accessed April 2, 2024.(REF-23992)​
  49. Medtronic and NVIDIA Collaborate to Build AI Platform for Medical Devices. NVIDIA. https://nvidianews.nvidia.com/news/medtronic-and-nvidia-collaborateto-build-ai-platform-for-medical-devices Published March 21, 2023. Accessed April 2, 2024(VV-00216)​
  50. ​Medtronic recognized for artificial intelligence innovation in 2023 AI Breakthrough Awards Program.AI breakthrough. Cision PR Web. https://www.prweb.com/releases/medtronic-recognized-for-artificial-intelligenceinnovation-in-2023-ai-breakthrough-awards-program-880484430.html Published June 21, 2023. Accessed April 2, 2024. (VV-00215) ​
  51. Prestigious NHS AI award paves way for real-world trial of GI GeniusTM intelligent endoscopy module (VV-00214)​
  52. GI Genius Module 100 and Module 200 [instructions for use]. Mansfield, MA: Medtronic; 2024​
  53. User Manual of software ColonPRO™ EU CPRO_UM_Master_LQ24070801_rev.1.0​
  54. Data on file​