Copyright
©The Author(s) 2021.
World J Gastroenterol. Oct 7, 2021; 27(37): 6191-6223
Published online Oct 7, 2021. doi: 10.3748/wjg.v27.i37.6191
Published online Oct 7, 2021. doi: 10.3748/wjg.v27.i37.6191
Ref. | Diagnostic Modality | AI classifier | Sizes of the training/validation sets | Outcomes | Performance |
Takiyama et al[33] | Esophago-gastro-duodenoscopy imaging | CNN | 1750/4357 | Anatomical classification among larynx, esophagus, stomach, and duodenum | 0.99-1.002,7 |
Pace et al[34] | Laboratory results, clinicopathological parameters | ANN | 159 patients | Diagnosis of gastroesophageal reflux disease | 67.86-1001,6 |
de Groof et al[35] | Esophageal endoscopic images | DNN | 1247/2976/807/807 patients | Classification of malignant from nondysplastic Barret’s esophagus | 88.21,6, 87.5-88.81,7, 87.63,6, 90.0-92.53,7, 88.64,6, 82.5-87.54,7 |
van der Sommen et al[36] | White-light endoscopic imaging | SVM | 44 patients with Barret’s esophagus | Diagnosis of early neoplastic lesions | Per image: 62-903,6, 65-904,6, Per patient: 52-1003,6, 74-964,6 |
Struyvenberg et al[37] | Volumetric laser endomicroscopy imaging | Several | 29 patients with Barret’s esophagus | Diagnosis of neoplastic lesions | 0.83-0.942,6 |
Swager et al[38] | Volumetric laser endomicroscopy imaging | Several | 60 images | Diagnosis of neoplastic lesions | 0.89-0.952,6 |
Kumagai et al[39] | Endocytoscopic imaging | CNN | 4715/15207 | Diagnosis of esophageal squamous cell carcinoma | 90.91,7, 0.72-0.902,7, 39.4-46.43,7, 98.2-98.44,7 |
Zheng et al[40] | Endoscopic images | CNN | 1507/452 patients | Diagnosis of H.pylori infection | 84.5-93.81,6, 0.93-0.972,6, 81.4-91.63,6, 90.1-98.64,6 |
Nakashima et al[41] | Endoscopic images | CNN | 162/60 patients | Diagnosis of H.pylori infection | 0.66-0.962,6 |
Itoh et al[42] | Endoscopic images | CNN | 149/30 images | Diagnosis of H.pylori infection | 0.9562,6, 86.73,6, 86.74,6 |
Shichijo et al[43] | Endoscopic images | CNN | 32308/114817 | Diagnosis of H.pylori infection | 83.1-87.71,7, 81.9-88.93,7, 83.4-87.44,7 |
Kanesaka et al[45] | NBI | SVM | 126/81 NBI images | Diagnosis of gastric cancer | 96.31,6, 96.73,6, 95.04,6 |
Hirasawa et al[46] | Endoscopic images | CNN | 13584/22967 | Diagnosis of gastric cancer | 92.23,7 |
Zhu et al[47] | Laboratory results, clinicopathological parameters, cancer biomarkers | GB/DT | 496/213 patients | Diagnosis of gastric cancer | 85.91,5, 831,6, 0.912,6, 883,5, 873,6, 83.44,5, 84.14,6 |
Tenório et al[48] | Laboratory results, clinicopathological parameters | Several | 178/38 | Diagnosis of celiac disease | 71.5-801,6, 0.71-0.842,6, 69-823,6, 67-804,6 |
Caetano Dos Santos et al[49] | Endomysial autoantibody test for IgA-class antibodies images | SVM | 2597 images (training:validation = 7:3) | Diagnosis of celiac disease | 96.8-98.851,6, 82.84-98.913,6, 98.81-99.404,6 |
Hujoel et al[50] | Laboratory results, clinicopathological parameters | Several | 408 undiagnosed patients | Diagnosis of celiac disease | 0.49-0.532,6 |
Manandhar et al[51] | Gut microbiome data | RF | 1429 fecal 16S metagenomic data subjects | Diagnosis of IBD | 0.80-0.822,6 |
Wei et al[52] | Single nucleotide polymorphisms data | Several | 60828 samples | Classifification of CD and UC | 0.782-0.8662,6 |
Mossotto et al[53] | Capsule endoscopy, histologic imaging | SVM | 239/487 pediatric patients | Classifification of CD, UC, and unclassified IBD | 71-82.71,5, 0.78-0.872,5, 83.31,7, 83-853,7 |
Xia et al[58] | Capsule endoscopy imaging | CNN | 697/1007 patients, 822590/2013657, images | Classification among different types of gastric lesions | 77.1-861,7, 0.80-0.902,7, |
Seguí et al[59] | Capsule endoscopy imaging | CNN | 50 videos | Classification of small bowel mobility events | 961,6 |
Park et al[60] | Capsule endoscopy imaging | CNN | 139 videos, 200000 images (training:validation:test = 6:2:2) | Small bowel lesion identification | 80.29-98.341,6, 0.9992,5, 0.9982,6,7 |
Hwang et al[61] | Capsule endoscopy imaging | CNN | 7556/57607 images | Classification of hemorrhagic and ulcerative lesions | 96.62-96.831,7, 95.07-97.613,7, 96.04-98.184,7 |
Otani et al[62] | Capsule endoscopy imaging | DNN | 167/407 patients | Classification among different types of small bowel lesions | 0.950-0.9962,6, 0.884-0.9282,7 |
Yuan et al[63] | Capsule endoscopy imaging | SVM | 20 patients, 340 images (training:validation = 8:2) | Diagnosis of peptic ulcers | 92.651,6, 94.123,6, 91.184,6 |
Karargyris et al[64] | Capsule endoscopy imaging | SVM | 80 frames | Diagnosis of peptic ulcers | 753,6, 73.34,6 |
He et al[65] | Capsule endoscopy imaging | CNN | 11 patients, 440000 images | Diagnosis of intestinal hookworms | 88.51,6, 0.8952,6, 84.63,6, 88.64,6 |
Leenhardt et al[66] | Capsule endoscopy imaging | CNN | 600/600 images | Diagnosis of gastrointestinal angiectasia | 1003,6, 964,6 |
Zhou et al[67] | Capsule endoscopy imaging | CNN | 21 videos | Diagnosis of celiac disease | 1003,6, 1004,6 |
Yamada et al[68] | Colon capsule endoscopy imaging | CNN | 15933/47847 | Diagnosis of colorectal neoplasias | 83.97, 0.9022,7, 793,7, 874,7 |
Wang et al[69] | Colonoscopy imaging | CNN | 5545 images/271137 images/6127 images/1387 videos/547 videos | Identification of colorectal polyps | 0.9842,7, 88.24-1003,7, 95.40-95.922,7 |
Misawa et al[70] | Colonoscopy imaging | CNN | 411/35 short videos | Identification of colorectal polyps | 76.51,6, 0.872,6, 903,6, 63.34,6 |
Urban G et al[71] | Colonoscopy imaging | CNN | 8641 images/207 videos | Identification of colorectal polyps | 96.41,7, 0.9912,7 |
Ozawa et al[72] | Colonoscopy imaging | CNN | 20431/70777 images | Identification of colorectal polyps, Classification of colorectal polyps | 90-973,7, 47-981,7 |
Mori et al[73] | NBI and methylene blue staining images | SVM | 466 diminutive polyps | Classification of diminutive rectosigmoid adenomas | NPV(%): 93.7-96.5 |
Tischendorf et al[74] | NBI | SVM | 209 colorectal polyps | Classification of colorectal polyps | 903,6, 70.24,6 |
Gross et al[75] | NBI | SVM | 434 colorectal polyps | Classification of small colorectal polyps | 93.11,6, 95.03,6, 90.34,6 |
Kominami et al[76] | NBI | SVM | 118 colorectal polyps | Classification of colorectal polyps | 93.21,6, 93.03,6, 93.34,6 |
Misawa et al[77] | NBI endocytoscopy | SVM | 979/100 endocytoscopy, images | Classification of colorectal polyps | 901,6, 84.53,6, 97.64,6 |
Takeda et al[78] | NBI endocytoscopy | SVM | 5543/200 endocytoscopy, images | Diagnosis of invasive CRC | 94.11,6, 89.43,6, 98.94,6 |
Chen et al[79] | NBI | CNN | 2157/2847 | Classification neoplastic from hyperplastic polyps | 96.33,7, 78.14,7, NPV(%): 91.57 |
Komeda et al[80] | NBI | CNN | 1200/600 images | Classification of adenomatous from non-adenomatous polyps | 75.11,6 |
Byrne et al[81] | NBI | CNN | 223/407 videos | Classification of adenomas from hyperplastic polyps | 941,7, 0.952,7, 983,7, 834,7, NPV(%): 977 |
- Citation: Christou CD, Tsoulfas G. Challenges and opportunities in the application of artificial intelligence in gastroenterology and hepatology. World J Gastroenterol 2021; 27(37): 6191-6223
- URL: https://www.wjgnet.com/1007-9327/full/v27/i37/6191.htm
- DOI: https://dx.doi.org/10.3748/wjg.v27.i37.6191