National Natural Science Foundation of China (NSFC) [81703166]; Science and Technology Program of Guangzhou [202002030445, 202002030086]; Natural Science Foundation of Guangdong Province [2019A1515011943]; China Postdoctoral Science Foundation [2020T130052ZX, 2019M662974]; Medical Scientific Research Foundation of Guangdong Province [A2020505, A2020499, B2021203, B2021139]
第一作者单位:[1]Southern Med Univ, Nanfang Hosp, Dept Radiat Oncol, Guangzhou 510515, Peoples R China[2]Southern Med Univ, Sch Publ Hlth, Dept Radiat Med, Guangzhou, Peoples R China
通讯作者:
通讯机构:[1]Southern Med Univ, Nanfang Hosp, Dept Radiat Oncol, Guangzhou 510515, Peoples R China[23]German Canc Res Ctr, Translat Radiat Oncol, Heidelberg, Germany[24]Heidelberg Univ, Sch Med, Heidelberg, Germany
推荐引用方式(GB/T 7714):
Zhou Zhaoming,Zhou Xiang,Cheng Liming,et al.Machine learning algorithms utilizing blood parameters enable early detection of immunethrombotic dysregulation in COVID-19[J].CLINICAL AND TRANSLATIONAL MEDICINE.2021,11(9):doi:10.1002/ctm2.523.
APA:
Zhou, Zhaoming,Zhou, Xiang,Cheng, Liming,Wen, Lei,An, Taixue...&Zhou, Cheng.(2021).Machine learning algorithms utilizing blood parameters enable early detection of immunethrombotic dysregulation in COVID-19.CLINICAL AND TRANSLATIONAL MEDICINE,11,(9)
MLA:
Zhou, Zhaoming,et al."Machine learning algorithms utilizing blood parameters enable early detection of immunethrombotic dysregulation in COVID-19".CLINICAL AND TRANSLATIONAL MEDICINE 11..9(2021)