540 related articles for article (PubMed ID: 32439090)
1. How Artificial Intelligence Will Impact Colonoscopy and Colorectal Screening.
Shung DL; Byrne MF
Gastrointest Endosc Clin N Am; 2020 Jul; 30(3):585-595. PubMed ID: 32439090
[TBL] [Abstract][Full Text] [Related]
2. Colorectal polyp characterization with standard endoscopy: Will Artificial Intelligence succeed where human eyes failed?
Parsa N; Rex DK; Byrne MF
Best Pract Res Clin Gastroenterol; 2021; 52-53():101736. PubMed ID: 34172255
[TBL] [Abstract][Full Text] [Related]
3. Artificial intelligence for identification and characterization of colonic polyps.
Parsa N; Byrne MF
Ther Adv Gastrointest Endosc; 2021; 14():26317745211014698. PubMed ID: 34263163
[TBL] [Abstract][Full Text] [Related]
4. Quality assurance of computer-aided detection and diagnosis in colonoscopy.
Vinsard DG; Mori Y; Misawa M; Kudo SE; Rastogi A; Bagci U; Rex DK; Wallace MB
Gastrointest Endosc; 2019 Jul; 90(1):55-63. PubMed ID: 30926431
[TBL] [Abstract][Full Text] [Related]
5. Artificial intelligence and computer-aided diagnosis in colonoscopy: current evidence and future directions.
Ahmad OF; Soares AS; Mazomenos E; Brandao P; Vega R; Seward E; Stoyanov D; Chand M; Lovat LB
Lancet Gastroenterol Hepatol; 2019 Jan; 4(1):71-80. PubMed ID: 30527583
[TBL] [Abstract][Full Text] [Related]
6. Artificial Intelligence Allows Leaving-In-Situ Colorectal Polyps.
Hassan C; Balsamo G; Lorenzetti R; Zullo A; Antonelli G
Clin Gastroenterol Hepatol; 2022 Nov; 20(11):2505-2513.e4. PubMed ID: 35835342
[TBL] [Abstract][Full Text] [Related]
7. Use of artificial intelligence in improving adenoma detection rate during colonoscopy: Might both endoscopists and pathologists be further helped.
Sinagra E; Badalamenti M; Maida M; Spadaccini M; Maselli R; Rossi F; Conoscenti G; Raimondo D; Pallio S; Repici A; Anderloni A
World J Gastroenterol; 2020 Oct; 26(39):5911-5918. PubMed ID: 33132644
[TBL] [Abstract][Full Text] [Related]
8. Artificial intelligence for colonoscopic polyp detection: High performance versus human nature.
East JE; Rittscher J
J Gastroenterol Hepatol; 2020 Oct; 35(10):1663-1664. PubMed ID: 33043510
[No Abstract] [Full Text] [Related]
9. Relationship between the polyp detection rate and the post-colonoscopy colorectal cancer rate.
Sastre Lozano VM; Morán Sánchez S; García Solano J; Conesa Zamora P; Ruiz Merino G
Rev Esp Enferm Dig; 2019 Aug; 111(8):598-602. PubMed ID: 31190550
[TBL] [Abstract][Full Text] [Related]
10. An overview of deep learning algorithms and water exchange in colonoscopy in improving adenoma detection.
Hsieh YH; Leung FW
Expert Rev Gastroenterol Hepatol; 2019 Dec; 13(12):1153-1160. PubMed ID: 31755802
[No Abstract] [Full Text] [Related]
11. Artificial intelligence-assisted colonoscopy: A review of current state of practice and research.
Taghiakbari M; Mori Y; von Renteln D
World J Gastroenterol; 2021 Dec; 27(47):8103-8122. PubMed ID: 35068857
[TBL] [Abstract][Full Text] [Related]
12. Artificial intelligence-aided colonoscopy: Recent developments and future perspectives.
Antonelli G; Gkolfakis P; Tziatzios G; Papanikolaou IS; Triantafyllou K; Hassan C
World J Gastroenterol; 2020 Dec; 26(47):7436-7443. PubMed ID: 33384546
[TBL] [Abstract][Full Text] [Related]
13. The application of artificial intelligence in improving colonoscopic adenoma detection rate: Where are we and where are we going.
Gan P; Li P; Xia H; Zhou X; Tang X
Gastroenterol Hepatol; 2023 Mar; 46(3):203-213. PubMed ID: 35489584
[TBL] [Abstract][Full Text] [Related]
14. Using of artificial intelligence: Current and future applications in colorectal cancer screening.
Zacharakis G; Almasoud A
World J Gastroenterol; 2022 Jun; 28(24):2778-2781. PubMed ID: 35979167
[TBL] [Abstract][Full Text] [Related]
15. Artificial Intelligence-Assisted Optical Diagnosis: A Comprehensive Review of Its Role in Leave-In-Situ and Resect-and-Discard Strategies in Colonoscopy.
El Zoghbi M; Shaukat A; Hassan C; Anderson JC; Repici A; Gross SA
Clin Transl Gastroenterol; 2023 Oct; 14(10):e00640. PubMed ID: 37747097
[TBL] [Abstract][Full Text] [Related]
16. Current status and future perspective on artificial intelligence for lower endoscopy.
Misawa M; Kudo SE; Mori Y; Maeda Y; Ogawa Y; Ichimasa K; Kudo T; Wakamura K; Hayashi T; Miyachi H; Baba T; Ishida F; Itoh H; Oda M; Mori K
Dig Endosc; 2021 Jan; 33(2):273-284. PubMed ID: 32969051
[TBL] [Abstract][Full Text] [Related]
17. Polyp Sizing Poster Improves Polyp Measurement but not Adenoma Detection Rates by Endoscopists in a Large Community Practice.
Shaukat A; Shamsi N; Menk J; Church TR; Rank J; Colton JB
Clin Gastroenterol Hepatol; 2019 Sep; 17(10):2034-2041. PubMed ID: 30312788
[TBL] [Abstract][Full Text] [Related]
18. Optical diagnosis of colorectal polyps using convolutional neural networks.
Kader R; Hadjinicolaou AV; Georgiades F; Stoyanov D; Lovat LB
World J Gastroenterol; 2021 Sep; 27(35):5908-5918. PubMed ID: 34629808
[TBL] [Abstract][Full Text] [Related]
19. Artificial intelligence technologies for the detection of colorectal lesions: The future is now.
Attardo S; Chandrasekar VT; Spadaccini M; Maselli R; Patel HK; Desai M; Capogreco A; Badalamenti M; Galtieri PA; Pellegatta G; Fugazza A; Carrara S; Anderloni A; Occhipinti P; Hassan C; Sharma P; Repici A
World J Gastroenterol; 2020 Oct; 26(37):5606-5616. PubMed ID: 33088155
[TBL] [Abstract][Full Text] [Related]
20. Overview of Deep Learning in Gastrointestinal Endoscopy.
Min JK; Kwak MS; Cha JM
Gut Liver; 2019 Jan; 13(4):388-393. PubMed ID: 30630221
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
