The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Artificial Intelligence-Assisted Polyp Detection for Colonoscopy: Initial Experience
Open accessAbstract
The adenoma detection rate is an established quality indicator for colonoscopy. For instance, a 1% increase in the adenoma detection rate was associated with a 3% decrease in interval colorectal cancer incidence.1 However, a previous meta-analysis showed that approximately 26% of neoplastic diminutive polyps were missed in single colonoscopy.2 Two factors are considered to affect this rate; one is blind spots and the other is human error. The first factor could be solved using a wide-angle scope or distal attachments, but human error is not easily overcome.
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Cites
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Adenoma detection rate and risk of colorectal cancer and death
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Cited by
Wang, P., Berzin, T. M., Glissen Brown, J. R., Bharadwaj, S., Becq, A., Xiao, X., Liu, P., Li, L., Song, Y., Zhang, D., et al. (2019) · Gut · doi:10.1136/gutjnl-2018-317500 · Cited by 865
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., et al. (2020) · Gastroenterology · doi:10.1053/j.gastro.2020.04.062 · Cited by 646
Signaling pathways involved in colorectal cancer: pathogenesis and targeted therapy
Li, Q., Geng, S., Luo, H., Wang, W., Mo, Y.-Q., Luo, Q., Wang, L., Song, G.-B., Sheng, J.-P., & Xu, B. (2024) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-024-01953-7 · Cited by 546
Application of artificial intelligence in gastroenterology
Yang, Y. J., & Bang, C. S. (2019) · World Journal of Gastroenterology · doi:10.3748/wjg.v25.i14.1666 · Cited by 263
Xu, H., Tang, R. S. Y., Lam, T. Y. T., Zhao, G., Lau, J. Y. W., Liu, Y., Wu, Q., Rong, L., Xu, W., Li, X., et al. (2023) · Clinical Gastroenterology and Hepatology · doi:10.1016/j.cgh.2022.07.006 · Cited by 209
Study on detection rate of polyps and adenomas in artificial-intelligence-aided colonoscopy
Huang, J., Liu, W.-N., Zhang, Y.-Y., Bian, X.-Q., Wang, L.-J., Yang, Q., & Zhang, X.-D. (2020) · Saudi Journal of Gastroenterology · doi:10.4103/sjg.sjg_377_19 · Cited by 179
Artificial intelligence and colonoscopy: Current status and future perspectives
Kudo, S., Mori, Y., Misawa, M., Takeda, K., Kudo, T., Itoh, H., Oda, M., & Mori, K. (2019) · Digestive Endoscopy · doi:10.1111/den.13340 · Cited by 147
Self-citationDiagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer
Zhou, D., Tian, F., Tian, X., Sun, L., Huang, X., Zhao, F., Zhou, N., Chen, Z., Zhang, Q., Yang, M., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-16777-6 · Cited by 123
Maassen, O., Fritsch, S., Palm, J., Deffge, S., Kunze, J., Marx, G., Riedel, M., Schuppert, A., & Bickenbach, J. (2021) · Journal of Medical Internet Research · doi:10.2196/26646 · Cited by 125
CAI4CAI: The Rise of Contextual Artificial Intelligence in Computer Assisted Interventions
Vercauteren, T., Unberath, M., Padoy, N., & Navab, N. (2020) · Proceedings of the IEEE · doi:10.1109/jproc.2019.2946993 · Cited by 125
Kamba, S., Tamai, N., Saitoh, I., Matsui, H., Horiuchi, H., Kobayashi, M., Sakamoto, T., Ego, M., Fukuda, A., Tonouchi, A., et al. (2021) · Journal of Gastroenterology · doi:10.1007/s00535-021-01808-w · Cited by 124
Gubatan, J., Levitte, S., Patel, A., Balabanis, T., Wei, M. T., & Sinha, S. R. (2021) · World Journal of Gastroenterology · doi:10.3748/wjg.v27.i17.1920 · Cited by 121
Artificial intelligence in gastrointestinal endoscopy: general overview
El Hajjar, A., & Rey, J.-F. (2020) · Chinese Medical Journal · doi:10.1097/cm9.0000000000000623 · Cited by 102
Barriers and pitfalls for artificial intelligence in gastroenterology: Ethical and regulatory issues
Ahmad, O. F., Stoyanov, D., & Lovat, L. B. (2020) · Techniques and Innovations in Gastrointestinal Endoscopy · doi:10.1016/j.tgie.2019.150636 · Cited by 78
Christou, C. D., & Tsoulfas, G. (2021) · World Journal of Gastroenterology · doi:10.3748/wjg.v27.i37.6191 · Cited by 54
Thakkar, S., Carleton, N. M., Rao, B., & Syed, A. (2020) · Gastroenterology · doi:10.1053/j.gastro.2019.12.035 · Cited by 47
Performance of ChatGPT on the Chinese postgraduate examination for clinical medicine: survey study
Yu, P., Fang, C., Liu, X., Fu, W., Ling, J., Yan, Z., Jiang, Y., Cao, Z., Wu, M., Chen, Z., et al. (2024) · JMIR Medical Education · doi:10.2196/48514 · Cited by 37
Artificial intelligence in colonoscopy: A review on the current status
Larsen, S. L. V., & Mori, Y. (2022) · DEN Open · doi:10.1002/deo2.109 · Cited by 21
Self-citationArtificial Intelligence-assisted colonoscopy and colorectal cancer screening: Where are we going?
Spadaccini, M., Troya, J., Khalaf, K., Facciorusso, A., Maselli, R., Hann, A., & Repici, A. (2024) · Digestive and Liver Disease · doi:10.1016/j.dld.2024.01.203 · Cited by 20
Use of Artificial Intelligence in the Diagnosis of Colorectal Cancer
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Metadata
- Authors
- Misawa, M., Kudo, S.-E., Mori, Y., Cho, T., Kataoka, S., Yamauchi, A., Ogawa, Y., Maeda, Y., Takeda, K., Ichimasa, K., Nakamura, H., Yagawa, Y., Toyoshima, N., Ogata, N., Kudo, T., Hisayuki, T., Hayashi, T., Wakamura, K., Baba, T., Ishida, F., Itoh, H., Roth, H., Oda, M., & Mori, K.
- Venue
- Gastroenterology
- Publisher
- Elsevier BV
- Published
- 2018-06
- Volume
- 154
- Issue
- 8
- Pages
- 2027-2029.e3
- ISSN
- 0016-5085 (ISSN-L)
- OpenAlex
- W2797069348
- Cited by
- 394
- References
- 3
- FWCI
- 15.92
- Type
- journal article
- Language
- en
- Open access
- hybrid
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