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For: Borrelli P, Kaboteh R, Enqvist O, Ulén J, Trägårdh E, Kjölhede H, Edenbrandt L. Artificial intelligence-aided CT segmentation for body composition analysis: a validation study. Eur Radiol Exp 2021;5:11. [PMID: 33694046 DOI: 10.1186/s41747-021-00210-8] [Cited by in Crossref: 11] [Cited by in F6Publishing: 11] [Article Influence: 5.5] [Reference Citation Analysis]
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4 Shirshin AV, Boikov IV, Malakhovskiy VN, Rameshvili TE, Kushnarev SV. Application of digital processing methods for automated cardiac segmentation from computed tomography data. Russian Military Medical Academy Reports 2022;41:49-54. [DOI: 10.17816/rmmar104344] [Reference Citation Analysis]
5 Gomez-Perez SL, Zhang Y, Byrne C, Wakefield C, Geesey T, Sclamberg J, Peterson S. Concordance of Computed Tomography Regional Body Composition Analysis Using a Fully Automated Open-Source Neural Network versus a Reference Semi-Automated Program with Manual Correction. Sensors (Basel) 2022;22. [PMID: 35591047 DOI: 10.3390/s22093357] [Reference Citation Analysis]
6 Aiello M, Baldi D, Esposito G, Valentino M, Randon M, Salvatore M, Cavaliere C. Evaluation of AI-Based Segmentation Tools for COVID-19 Lung Lesions on Conventional and Ultra-low Dose CT Scans. Dose-Response 2022;20:155932582210828. [DOI: 10.1177/15593258221082896] [Reference Citation Analysis]
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8 Huang Y, Tsai Y, Lin P, Yeh Y, Hsu Y, Wu P, Shen M, Shi Z. The Value of Artificial Intelligence-Assisted Imaging in Identifying Diagnostic Markers of Sarcopenia in Patients with Cancer. Disease Markers 2022;2022:1-14. [DOI: 10.1155/2022/1819841] [Reference Citation Analysis]
9 M. Scholz A, Kusec G, D. Mitchell A, Baulain U. Tracing the Inside of Pigs Non-Invasively: Recent Developments. Tracing the Domestic Pig [Working Title] 2021. [DOI: 10.5772/intechopen.101740] [Reference Citation Analysis]
10 Paravastu SS, Hasani N, Farhadi F, Collins MT, Edenbrandt L, Summers RM, Saboury B. Applications of Artificial Intelligence in 18F-Sodium Fluoride Positron Emission Tomography/Computed Tomography:: Current State and Future Directions. PET Clin 2022;17:115-35. [PMID: 34809861 DOI: 10.1016/j.cpet.2021.09.012] [Reference Citation Analysis]
11 Ying T, Borrelli P, Edenbrandt L, Enqvist O, Kaboteh R, Trägårdh E, Ulén J, Kjölhede H. Automated artificial intelligence-based analysis of skeletal muscle volume predicts overall survival after cystectomy for urinary bladder cancer. Eur Radiol Exp 2021;5:50. [PMID: 34796422 DOI: 10.1186/s41747-021-00248-8] [Reference Citation Analysis]
12 Zhou Z, Xiong Z, Xie Q, Xiao P, Zhang Q, Gu J, Li J, Hu D, Hu X, Shen Y, Li Z. Computed tomography-based multiple body composition parameters predict outcomes in Crohn's disease. Insights Imaging 2021;12:135. [PMID: 34564786 DOI: 10.1186/s13244-021-01083-6] [Cited by in Crossref: 1] [Cited by in F6Publishing: 3] [Article Influence: 0.5] [Reference Citation Analysis]