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10.1002/ar.24888 http://scihub22266oqcxt.onion/10.1002/ar.24888 35263033!9082487!35263033     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 251.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\35263033.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Anat+Rec+(Hoboken) 2023 ; 306 (12): 2984-2996 Nephropedia Template TP {{tp|p=35263033|t=2023. Data-mining-based of ancient traditional Chinese medicine records from 475 BC to 1949 to potentially treat COVID-19 |pdf=|usr=}}{{35263033}} gab.com Text Data-mining-based of ancient traditional Chinese medicine records from 475 BC to 1949 to potentially treat COVID-19 JO: Anat Rec (Hoboken) http://www.kidney.de/pget.php?&tw=1&pmid=35263033 #FOAvip Traditional Chinese Medicine (TCM) plays a role in preventing and treating COVID-19 in China. Based on the manifestations and symptoms of COVID-19, our study used the data mining method to summarize related therapeutic experience left by predecessors who used TCM to treat epidemics in their eras. Initially, we collected abundant medical records with similar manifestations of COVID-19 in Chinese ancient times. The key words including wen (), yi (), li (), and zhang () were searched in ZhongyiZhiku (https://www.zk120.com/) from Warring States Period (475 BC-221 BC) to the Republic of China era (1912-1949) to locate ancient medical records according to inclusion criteria and exclusion criteria. Moreover, COVID-19-related manifestations and corresponding medications in those records were categorized. Eventually, Traditional Chinese Medicine Inheritance Support System version 2.5 was used to build a medical record database of TCM treating COVID-19. Our study collected 263 epidemic medical records comprising COVID-19 related manifestations and found that Chinese Materia Medica (CMM) combinations excavated from ancient medical records included Ren Shen Bai Du San, Wu Ling San, Xiao Chai Hu Tang, Da Cheng Qi Tang, Da Chai Hu Tang, Ling Gui Zhu Gan Tang, and Qing Wen Bai Du Yin. The recurrent CMMs with a high frequency for treating COVID-19 manifestations were Scutellariae Radix (Huang Qin), Paeoniae Alba Radix (Bai Shao), Poria (Fu Ling), and Bupleuri Radix (Chai Hu). Our study suggests that TCM might offer new therapeutic strategies for COVID-19. Twit Text FOAVip Data-mining-based of ancient traditional Chinese medicine records from 475 BC to 1949 to potentially treat COVID-19 ????Anat Rec (Hoboken) http://www.kidney.de/pget.php?&tw=1&pmid=35263033 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35263033 #FOAvip English Wikipedia <ref>{{Cite pmid|35263033}}</ref> Data-mining-based of ancient traditional Chinese medicine records from 475 BC to 1949 to potentially treat COVID-19 #MMPMID35263033 Han Y; Yang Z; Fang S; Zhang M; Xie Z; Fan Y; Zhao T Anat Rec (Hoboken) 2023[Dec]; 306 (12): 2984-2996 PMID35263033show ga Traditional Chinese Medicine (TCM) plays a role in preventing and treating COVID-19 in China. Based on the manifestations and symptoms of COVID-19, our study used the data mining method to summarize related therapeutic experience left by predecessors who used TCM to treat epidemics in their eras. Initially, we collected abundant medical records with similar manifestations of COVID-19 in Chinese ancient times. The key words including wen (), yi (), li (), and zhang () were searched in ZhongyiZhiku (https://www.zk120.com/) from Warring States Period (475 BC-221 BC) to the Republic of China era (1912-1949) to locate ancient medical records according to inclusion criteria and exclusion criteria. Moreover, COVID-19-related manifestations and corresponding medications in those records were categorized. Eventually, Traditional Chinese Medicine Inheritance Support System version 2.5 was used to build a medical record database of TCM treating COVID-19. Our study collected 263 epidemic medical records comprising COVID-19 related manifestations and found that Chinese Materia Medica (CMM) combinations excavated from ancient medical records included Ren Shen Bai Du San, Wu Ling San, Xiao Chai Hu Tang, Da Cheng Qi Tang, Da Chai Hu Tang, Ling Gui Zhu Gan Tang, and Qing Wen Bai Du Yin. The recurrent CMMs with a high frequency for treating COVID-19 manifestations were Scutellariae Radix (Huang Qin), Paeoniae Alba Radix (Bai Shao), Poria (Fu Ling), and Bupleuri Radix (Chai Hu). Our study suggests that TCM might offer new therapeutic strategies for COVID-19. |*COVID-19[MESH] |*Data Mining[MESH] |*Medicine, Chinese Traditional[MESH] |China[MESH]Data-mining-based of ancient traditional Chinese medicine records from(epmc).pdf DeepDyve Pubget Overpricing