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©The Author(s) 2022.
Artif Intell Gastroenterol. Apr 28, 2022; 3(2): 28-35
Published online Apr 28, 2022. doi: 10.35712/aig.v3.i2.28
Published online Apr 28, 2022. doi: 10.35712/aig.v3.i2.28
Ref. | Type of paper | Main topic | AI implementation |
Decharatanachart et al[4], 2021 | Meta-analysis | Chronic liver diseases | Diagnosis and staging of liver fibrosis without biopsy |
Christou et al[5], 2021 | Review | IBD, GI bleeding and chronic liver diseases | Increasing accuracy of gold standard diagnostic exams |
Park et al[15], 2020 | Review | Liver diseases | Staging of liver disease and prognosis after liver resection or chemotherapy |
Wang et al[16], 2012 | Survey | Liver imaging | Diagnosis of structural changes in healthy liver |
Shan et al[19], 2019 | Research article | Liver imaging (CT) | Prediction of early recurrence after HCC resection/RF |
Hu et al[18], 2019 | Research article | Liver imaging (US) | Evaluating microvascular invasion in HCC |
Iranmanesh et al[19], 2014 | Research article | Liver imaging (CT) | Evaluating portal pressure without invasive methods |
Wang et al[23], 2019 | Research article | Liver imaging (CT/MRI) | Using liver segmentation to an automatized liver biometry |
Fang et al[21], 2020 | Research article | Liver imaging | Using liver segmentation to more accurate localization of a hepatic lesion |
Winkel et al[22], 2020 | Comparative study | Liver imaging | Comparing a fully automated liver segmentation to a manual one |
Zhou et al[23], 2019 | Review | Liver imaging | Detecting hepatic lesions, characterized them and evaluate a response after treatment |
Yasaka et al[24], 2018 | Retrospective study | Liver imaging (CT) | Differentiation between benign and malignant hepatic lesions |
Guo et al[25], 2018 | Research article | Liver imaging (US) | Differentiation between benign and malignant hepatic lesions |
Schmauch et al[26], 2019 | Research article | Liver imaging (US) | Differentiation between benign and malignant hepatic lesions |
Tiyarattanachai et al[27], 2021 | Retrospective study | Liver imaging (US) | Detect and diagnose hepatic lesions |
Perez et al[28], 2020 | Review | HCC | Improving diagnosis and evaluation after ancillary treatments |
Vivanti et al[29], 2017 | Research article | Liver neoplasia | Evaluating post chemotherapy response |
Li et al[30], 2015 | Research article | Liver imaging (CT) | Differentiation between benign and malignant hepatic lesions |
Hamm et al[31], 2019 | Research article | Liver imaging (MRI) | Differentiation between benign and malignant hepatic lesions |
Zhang et al[32], 2018 | Research article | HCC | Differentiation between healthy and tumoral tissue in patient's liver |
Preis et al[33], 2011 | Research article | Liver imaging (PET) | Differentiation between benign and malignant hepatic lesions |
Chen et al[34], 2020 | Review | Liver surgery | Implementation in pre and post operative care |
Nakayama et al[35], 2017 | Retrospective study | Liver surgery | Use of 3D modeling to improve hepatice resection |
Zhang et al[36], 2018 | Prospective study | Liver surgery | Diagnosis and treatment of perihilar CCC |
Vorontsov et al[37], 2019 | Retrospective study | Liver surgery | Improving CRM identification and segmentation |
Chartrand et al[39], 2017 | Comparative study | Liver imaging | Improving liver segmentation and volumetry |
Cancian et al[40], 2021 | Research article. | Liver pathology | Better assessment pf tumor microenvironment |
- Citation: Tonini V, Vigutto G, Donati R. Liver surgery for colorectal metastasis: New paths and new goals with the help of artificial intelligence. Artif Intell Gastroenterol 2022; 3(2): 28-35
- URL: https://www.wjgnet.com/2644-3236/full/v3/i2/28.htm
- DOI: https://dx.doi.org/10.35712/aig.v3.i2.28