For: | Li XF, Huang YZ, Tang JY, Li RC, Wang XQ. Development of a random forest model for hypotension prediction after anesthesia induction for cardiac surgery. World J Clin Cases 2021; 9(29): 8729-8739 [PMID: 34734051 DOI: 10.12998/wjcc.v9.i29.8729] |
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URL: | https://www.wjgnet.com/2307-8960/full/v9/i29/8729.htm |
Number | Citing Articles |
1 |
Pietro Arina, Maciej R. Kaczorek, Daniel A. Hofmaenner, Walter Pisciotta, Patricia Refinetti, Mervyn Singer, Evangelos B. Mazomenos, John Whittle. Prediction of Complications and Prognostication in Perioperative Medicine: A Systematic Review and PROBAST Assessment of Machine Learning Tools. Anesthesiology 2024; 140(1): 85 doi: 10.1097/ALN.0000000000004764
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2 |
Romain PIRRACCHIO. The past, the present and the future of machine learning and artificial intelligence in anesthesia and Postanesthesia Care Units (PACU). Minerva Anestesiologica 2022; 88(11) doi: 10.23736/S0375-9393.22.16518-1
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3 |
F Gheysen, S Rex. Artificial intelligence in anesthesiology. Acta Anaesthesiologica Belgica 2023; 74(3): 185 doi: 10.56126/75.3.21
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4 |
Ida Mohammadi, Shahryar Rajai Firouzabadi, Melika Hosseinpour, Mohammadhosein Akhlaghpasand, Bardia Hajikarimloo, Roozbeh Tavanaei, Amirreza Izadi, Sam Zeraatian-Nejad, Foolad Eghbali. Predictive ability of hypotension prediction index and machine learning methods in intraoperative hypotension: a systematic review and meta-analysis. Journal of Translational Medicine 2024; 22(1) doi: 10.1186/s12967-024-05481-4
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5 |
Ramakrishna Mukkamala, Michael P. Schnetz, Ashish K. Khanna, Aman Mahajan. Intraoperative Hypotension Prediction: Current Methods, Controversies, and Research Outlook. Anesthesia & Analgesia 2024; doi: 10.1213/ANE.0000000000007216
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6 |
Shinichi Tamaru, Hirotsugu Suwanai, Hironori Abe, Junko Sasaki, Keitaro Ishii, Hajime Iwasaki, Jumpei Shikuma, Rokuro Ito, Takashi Miwa, Toru Sasaki, Tomoko Takamiya, Shigeru Inoue, Kazuhiro Saito, Masato Odawara, Ryo Suzuki. Machine learning approach to predict subtypes of primary aldosteronism is helpful to estimate indication of adrenal vein sampling. High Blood Pressure & Cardiovascular Prevention 2022; 29(4): 375 doi: 10.1007/s40292-022-00523-8
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7 |
Ying Zhao, Zhe Tao, Ying Li, Huige Sun, Jingrui Tang, Qianya Wang, Liang Guo, Weiwei Song, Bailian Larry Li. Prediction of municipal solid waste generation and analysis of dominant variables in rapidly developing cities based on machine learning – a case study of China. Waste Management & Research: The Journal for a Sustainable Circular Economy 2024; 42(6): 476 doi: 10.1177/0734242X231192766
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8 |
Guangshan Jin, Fuqiang Liu, Yiwen Yang, Jiahui Chen, Qian Wen, Yudong Wang, Ling Yu, Jianhua He. Carotid blood flow changes following a simulated end-inspiratory occlusion maneuver measured by ultrasound can predict hypotension after the induction of general anesthesia: an observational study. BMC Anesthesiology 2024; 24(1) doi: 10.1186/s12871-023-02393-6
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9 |
Sana Hashemi, Zohreh Yousefzadeh, Ahmad Ali Abin, Azar Ejmalian, Shahabedin Nabavi, Ali Dabbagh. Machine Learning-Guided Anesthesiology: A Review of Recent Advances and Clinical Applications. Journal of Cellular & Molecular Anesthesia 2024; 9(1) doi: 10.5812/jcma-145369
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10 |
Esmée C. de Boer, Joris van Houte, Catarina Dinis Fernandes, Jens Muehlsteff, R. Arthur Bouwman, Massimo Mischi. Predicting Hypotension After Spinal Anesthesia Using Carotid Ultrasound and Clinical Variables. 2024 IEEE International Symposium on Medical Measurements and Applications (MeMeA) 2024; : 1 doi: 10.1109/MeMeA60663.2024.10596875
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