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For: Lee S, Summers RM. Clinical Artificial Intelligence Applications in Radiology: Chest and Abdomen. Radiol Clin North Am 2021;59:987-1002. [PMID: 34689882 DOI: 10.1016/j.rcl.2021.07.001] [Cited by in Crossref: 5] [Cited by in F6Publishing: 6] [Article Influence: 2.5] [Reference Citation Analysis]
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1 Dreizin D, Staziaki PV, Khatri GD, Beckmann NM, Feng Z, Liang Y, Delproposto ZS, Klug M, Spann JS, Sarkar N, Fu Y. Artificial intelligence CAD tools in trauma imaging: a scoping review from the American Society of Emergency Radiology (ASER) AI/ML Expert Panel. Emerg Radiol 2023. [PMID: 36917287 DOI: 10.1007/s10140-023-02120-1] [Reference Citation Analysis]
2 Agrawal A, Khatri GD, Khurana B, Sodickson AD, Liang Y, Dreizin D. A survey of ASER members on artificial intelligence in emergency radiology: trends, perceptions, and expectations. Emerg Radiol 2023. [PMID: 36913061 DOI: 10.1007/s10140-023-02121-0] [Reference Citation Analysis]
3 Aisen AM, Rodrigues PS. Deep Learning to Detect Pancreatic Cancer at CT: Artificial Intelligence Living Up to Its Hype. Radiology 2023;306:183-5. [PMID: 36098644 DOI: 10.1148/radiol.222126] [Reference Citation Analysis]
4 Toda N, Hashimoto M, Iwabuchi Y, Nagasaka M, Takeshita R, Yamada M, Yamada Y, Jinzaki M. Validation of deep learning-based computer-aided detection software use for interpretation of pulmonary abnormalities on chest radiographs and examination of factors that influence readers' performance and final diagnosis. Jpn J Radiol 2023;41:38-44. [PMID: 36121622 DOI: 10.1007/s11604-022-01330-w] [Reference Citation Analysis]
5 van Beek EJR, Ahn JS, Kim MJ, Murchison JT. Validation study of machine-learning chest radiograph software in primary and emergency medicine. Clin Radiol 2023;78:1-7. [PMID: 36171164 DOI: 10.1016/j.crad.2022.08.129] [Reference Citation Analysis]
6 Palm V, Norajitra T, von Stackelberg O, Heussel CP, Skornitzke S, Weinheimer O, Kopytova T, Klein A, Almeida SD, Baumgartner M, Bounias D, Scherer J, Kades K, Gao H, Jäger P, Nolden M, Tong E, Eckl K, Nattenmüller J, Nonnenmacher T, Naas O, Reuter J, Bischoff A, Kroschke J, Rengier F, Schlamp K, Debic M, Kauczor H, Maier-hein K, Wielpütz MO. AI-Supported Comprehensive Detection and Quantification of Biomarkers of Subclinical Widespread Diseases at Chest CT for Preventive Medicine. Healthcare 2022;10:2166. [DOI: 10.3390/healthcare10112166] [Reference Citation Analysis]
7 Ahuja A, Kefalakes H. Clinical Applications of Artificial Intelligence in Gastroenterology: Excitement and Evidence. Gastroenterology 2022;163:341-4. [PMID: 35489435 DOI: 10.1053/j.gastro.2022.04.025] [Reference Citation Analysis]
8 Fang Z, Peltz G. An automated multi-modal graph-based pipeline for mouse genetic discovery. Bioinformatics 2022;38:3385-94. [PMID: 35608290 DOI: 10.1093/bioinformatics/btac356] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]