GI Genius™ intelligent endoscopy module.

GI Genius™ is the first-to-market, deep learning, computer-aided polyp detection system, able to detect polyps of different shapes, sizes and morphologies in real time.

Medtronic is the sole distributor,
marketer and owner of GI Genius trademarks.

Harnessing AI to detect the undetected.

Powered by Artificial Intelligence, the GI Genius™ intelligent endoscopy module offers a transformative solution to address challenges in colorectal screening. Integrating seamlessly with existing endoscopy processes, it harnesses deep learning algorithms to assist in clinical decision-making in real time, using visual markers to alert physicians to the presence of lesions.

+ 30 %

Relative increase in ADR. 1

- 50 %

Reduction in missed polyps. 2

+ 53 %

More likely to detect polyps in the distal colon. 1

The genesis of genius: what makes GI Genius™ special?


GI Genius™ was designed to assist physicians in a truly transformative way. That’s why it earned a place in the FORTUNE 2022 ‘Change the World’ list.


The development of GI Genius™ was driven from the outset by scientific investigation, ensuring its effectiveness and facilitating regulatory approval.


The deep learning algorithms of the GI Genius™ module are trained on a robust data-set of 13 million images of polyp of multiple shapes and sizes.


When AI and humans work together, they are more effective than either is alone. That is why GI Genius™ is designed to assist physicians, not replace them.

"The accuracy achieved by the hybrid AI-endoscopist team is higher than the accuracy of the endoscopist alone, or the AI alone."
Andrea Cherubini, PhD

SVP Science, AI and Data, Cosmo IMD

99.7 %

Per-lesion sensitivity. 3

82.2 %

Faster polyp recognition than the endoscopist. 3

< 1 %

False activations. 3

Seamless integration.
Universal compatibility.


Your existing endoscopy tower and high-definition endoscope is all you need to integrate with the GI Genius™ intelligent endoscopy module.


GI Genius™ intelligent endoscopy module can be easily integrated with existing major brands of endoscopic processors.


GI Genius™ intelligent endoscopy module simply connects to the existing endoscope, video processor, and display monitor.


Turn on GI Genius™ intelligent endoscopy module and immediately experience the benefits of AI, without changing any part of your procedure.

Hardware and software designed for today, and ready for tomorrow.

Artificial Intelligence is resource intensive, and its applicability may evolve over time. That’s why the GI GeniusTM hardware platform is built to be both powerful and flexible, and it’s why the software that operates on it can be easily updated and upscaled. So GI Genius™ is ready for whatever opportunities the future may bring.

Scientific evidence

White light computer-aided optical diagnosis of diminutive colorectal polyps in routine clinical practice

Rondonotti, E., Bergna, I.M.B., Paggi, S., Amato, A., Andrealli, A., Scardino, G., Tamanini, G., Lenoci, N., Mandelli, G., Terreni, N., Rocchetto, S., Piagnani, A., Di Paolo, D., Bina, N., Filippi, E., Ambrosiani, L., Hassan, C., Correale, L., Radaelli, F., 2024

REAL-Colon: A dataset for developing real-world AI applications in colonoscopy.

Biffi, C., Antonelli, G., Bernhofer, S., Hassan, C., Hirata, D., Iwatate, M., Maieron, A., Salvagnini, P., Cherubini, A., 2024.

The Efficacy of Real-Time Computer-Aided Detection of Colonic Neoplasia In Community Practice: A Pragmatic Randomized Controlled Trial.

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

A Computer-Aided Detection (CADe) System Significantly Improves Polyp Detection in Routine Practice.

Keswani, R.N., Thakkar, U., Sals, A., Pandolfino, J.E., 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.

Cherubini A., Ngo Dinh, N. 2023

Effect of real-time computer-aided detection of colorectal adenoma in routine colonoscopy (COLO-GENIUS): a single-centre randomised controlled trial

Karsenti, D., Tharsis, G., Perrot, B., Cattan, P., Percie du Sert, A., Venezia, F., Zrihen, E., Gillet, A., Lab, J.P., Tordjman, G., Cavicchi, M. 2023

Role of Artificial Intelligence in Colonoscopy Detection of Advanced Neoplasias

Mangas-Sanjuan, C., de-Castro, L., Cubiella, J., Díez-Redondo, P., Suárez, A., Pellisé, M., Fernández, N., Zarraquiños, S., Núñez-Rodríguez, H., Álvarez-García, V., Ortiz, O., Sala-Miquel, N., Zapater, P., Jover, R.; CADILLAC study investigators*, 2023

Direct comparison of multiple computer-aided polyp detection systems

Troya, J., Sudarevic, B., Krenzer, A., Banck, M., Brand, M., Walter, B.M., Puppe, F., Zoller, W.G., Meining, A., Hann, A., 2023

Gorilla in the room: Even experts can miss polyps at colonoscopy and how AI helps complex visual perception tasks

Cherubini, A. and East, J.E. 2023

Cost-effectiveness of Artificial Intelligence-Aided Colonoscopy for Adenoma Detection in Colon Cancer Screening

Barkun, A.N., von Renteln, D., Sadri, H. 2023

Combination of mucosa-exposure device and computer-aided detection for Adenoma Detection during Colonoscopy: a randomized trial

Spadaccini, M., Hassan, C., Rondonotti, E., Antonelli, G., Andrisani, G., Lollo, G., Auriemma, F., Iacopini, F., Facciorusso, A., Maselli, R., Fugazza, A., Bergna, I.M.B., Cereatti, F., Mangiavillano, B., Radaelli, F., Di Matteo, F., Gross, S.A., Sharma, P., Mori, Y., Bretthauer, M., Rex, D.K., Repici, A. 2023

The brave new world of artificial intelligence: dawn of a new era

Di Napoli, G., Lee, L. S., 2023

Cost-utility analysis of real-time artificial intelligent-assisted colonoscopy in Italy

Hassan, C., Povero, M., Pradelli, L., Spadaccini, M., Repici, A., 2023

Knowledge, perceptions and behaviours of endoscopists towards the use of artificial intelligence-aided colonoscopy.

Tham, S., Koh, F.H., Teo, E.K., Lin, C.L., Foo, F.J., 2023

An Evaluation of Critical Factors for the Cost-Effectiveness of Real-Time Computer-Aided Detection: Sensitivity and Threshold Analyses Using a Microsimulation Model

Thiruvengadam, N.R., Cote, G., Gupta, S., Rodrigues, M., Schneider, Y., Arain, M.A., Solaimani, P., Serrao, S., Kochman, M.L., Saumoy, M., 2023

Impact of Artificial Intelligence on Miss Rate of Colorectal Neoplasia

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., Ciofoaia, V., Arndtz, S., Cangemi, D., Puddick, K., Derfus, G., Johal, A.S., Barawi, M., Longo, L., Moro, L., Repici, A., Hassan, C., 2022

A novel AI device for real-time optical characterization of colorectal polyps

Biffi, C., Salvagnini, P., Dinh, N.N., Hassan, C., Sharma, P., GI Genius CADx Study Group, Cherubini, A., 2022

Artificial Intelligence Allows Leaving-In-Situ Colorectal Polyps. Clin. Gastroenterol. Hepatol. Off. Clin. Pract. J. Am. Gastroenterol

Hassan, C., Balsamo, G., Lorenzetti, R., Zullo, A., Antonelli, G., 2022

Experimental evidence of effective human-AI collaboration in medical decision-making

Reverberi, C., Rigon, T., Solari, A., Hassan, C., Cherubini, P., GI Genius CADx Study Group, Cherubini, A., 2022

Strengths and Weaknesses of an Artificial Intelligence Polyp Detection Program as Assessed by a High-Detecting Endoscopist

Rex, D.K., Mori, Y., Sharma, P., Lahr, R.E., Vemulapalli, K.C., Hassan, C., 2022

Artificial intelligence and colonoscopy experience: lessons from two randomised trials

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., Radaelli, F., Savevski, V., Wallace, M.B., Sharma, P., Rösch, T., Hassan, C., 2022

Evaluation of a real-time computer-aided polyp detection system during screening colonoscopy: AI-DETECT study

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., 2022

Artificial Intelligence-Aided Colonoscopy Does Not Increase Adenoma Detection Rate in Routine Clinical Practice

Levy, I., Bruckmayer, L., Klang, E., Ben-Horin, S., Kopylov, U., 2022

Computer-aided Detection of Polyps Does Not Improve Colonoscopist Performance in a Pragmatic Implementation Trial

Ladabaum, U., Shepard, J., Weng, Y., Desai, M., Singer, S.J., Mannalithara, A., 2022

Prospective study of computer-aided detection of colorectal adenomas in hospitalized patients

Engelke, C., Graf, M., Maass, C., Tews, H.C., Kraus, M., Ewers, T., Sayk, F., Solbach, P., Zimpel, C., Tharun, L., Marquardt, J.U., Kirstein, M.M., 2022

One-year review of real-time artificial intelligence (AI)-aided endoscopy performance

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

Real-time artificial intelligence (AI)-aided endoscopy improves adenoma detection rates even in experienced endoscopists: a cohort study in Singapore

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

Discovering the first US FDA-approved computer-aided polyp detection system

Spadaccini, M., Marco, A.D., Franchellucci, G., Sharma, P., Hassan, C., Repici, A., 2022

Computer-aided detection-assisted colonoscopy: classification and relevance of false positives

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

New artificial intelligence system: first validation study versus experienced endoscopists for colorectal polyp detection

Hassan, C., Wallace, M.B., Sharma, P., Maselli, R., Craviotto, V., Spadaccini, M., Repici, A., 2020

Efficacy of Real-Time Computer-Aided Detection of Colorectal Neoplasia in a Randomized Trial

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., Wallace, M., Sharma, P., Rosch, T., Hassan, C., 2020

GI Genius™ is distributed
by Medtronic.

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