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nexusstc/Advanced statistical tools and machine learning applied to elemental analysis associated with medical conditions/3b2d5b76f7a6b8a08f162936892a1fc8.pdf
Advanced statistical tools and machine learning applied to elemental analysis associated with medical conditions 🔍
George L. Donati Elsevier Pub. Co, ICP-MS and Trace Element Analysis as Tools for Better Understanding Medical Conditions, 2022
英语 [en] · PDF · 2.3MB · 2022 · 🤨 其他 · nexusstc · Save
描述
ICP-MS and Trace Element Analysis as Tools for Better Understanding Medical Conditions, Volume 97 discusses trace elements and how they play an important role in biological functions and metabolism in the human body. Chapters cover Biomedical analysis by ICP-MS: A focus on single cell, Advanced statistical tools and machine learning applied to trace element analysis associated with medical conditions, ICP-MS as a tool to understand trace element homeostasis in neurological disorders, High-precision isotopic analysis of essential mineral elements – possibilities for medical diagnosis and prognosis, Exploring ICP-MS as a versatile technique: From imaging to chemical speciation, and more. Discusses the latest diagnosis/pathologies using ICP-MS analysis Covers metals, isotopes and metalorganic species for medical conditions Includes ICP-MS-based techniques
备选标题
ICP-MS and Trace Element Analysis As Tools for Better Understanding Medical Conditions
备选标题
Comprehensive analytical chemistry
备选作者
Marco Aurelio Zezzi-Arruda, Jemmyson Romario de Jesus, Jemmyson Romário de Jesus
备选作者
Marco Aurélio Zezzi Arruda; Jemmyson Romário de Jesus
备选作者
Cecil L Wilson; David W Wilson; G Svehla
备用出版商
Wolters Kluwer Legal & Regulatory U.S.
备用出版商
Aspen Publishers
备用版本
Comprehensive analytical chemistry (Print), Volume 97, 2022
备用版本
Comprehensive analytical chemistry, Amsterdam, 2022
备用版本
United States, United States of America
备用版本
Elsevier Ltd., [N.p.], 2022
备用版本
Amsterdam ; New York, 1959-
元数据中的注释
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元数据中的注释
Referenced by: doi:10.1023/a:1010933404324 doi:10.1126/science.290.5500.2319 doi:10.18637/jss.v033.i01 doi:10.1126/science.220.4598.671 doi:10.18637/jss.v036.i11 doi:10.1007/bf00994018 doi:10.1111/j.1467-9868.2005.00503.x doi:10.1126/science.1136800 doi:10.1016/s0031-3203(99)00137-5 doi:10.1037/h0071325 doi:10.1162/089976698300017467 doi:10.1080/1047322x.1990.10389587 doi:10.1016/0031-3203(89)90067-8 doi:10.1093/biomet/58.3.453 doi:10.1016/j.compbiomed.2019.103375 doi:10.1007/s10994-019-05855-6 doi:10.1080/15459620490462797 doi:10.1016/0169-7439(87)80084-9 doi:10.1073/pnas.0500334102 doi:10.1023/a:1012487302797 doi:10.1371/journal.pone.0011252 doi:10.1351/goldbook doi:10.1016/j.aca.2015.08.053 doi:10.2202/1544-6115.1691 doi:10.1016/s0031-3203(99)00216-2 doi:10.1016/j.trac.2020.116094 doi:10.1016/j.eswa.2018.08.002 doi:10.1016/j.eswa.2019.05.028 doi:10.1039/c2ay05705k doi:10.1002/env.2193 doi:10.1007/s00018-008-8189-9 doi:10.1021/acs.jproteome.7b00055 doi:10.1038/nmeth.4438 doi:10.1039/c8an00599k doi:10.1016/s0167-9473(02)00224-4 doi:10.1364/boe.421961 doi:10.1177/2374289519873088 doi:10.1371/journal.pcbi.1006907 doi:10.1016/j.jtemb.2021.126733 doi:10.1007/s12011-008-8279-4 doi:10.1007/3-540-35978-8_30 doi:10.1016/j.compbiomed.2014.04.012 doi:10.1177/0962280217727033 doi:10.1007/s12011-018-1326-x doi:10.1039/c5mt00050e doi:10.1007/bf02698010 doi:10.1016/j.aca.2010.12.028 doi:10.1007/s12011-010-8748-4 doi:10.1016/s0003-2670(01)00923-0 doi:10.1088/1752-7155/3/4/046003 doi:10.1351/pac200880122577 doi:10.1016/j.cca.2015.11.014 doi:10.1039/c7ja00103g doi:10.1016/j.ygeno.2019.07.002 doi:10.1016/j.jpba.2016.02.019 doi:10.1007/s10462-004-2901-4 doi:10.1039/c2mt00178k doi:10.1016/j.jtemb.2019.09.009 doi:10.1039/c8ja00341f doi:10.1016/j.talanta.2018.12.061 doi:10.1007/s00216-015-8504-x doi:10.1016/j.chemolab.2021.104248 doi:10.1093/mtomcs/mfab018
备用描述
1. Elemental determination for clinical diagnosis and prognosis: challenges and trends in sample preparation / Marcia Foster Mesko, Alessandra Schneider Henn, Diogo la Rosa Novo, Ethel Antunes Wilhelm, and Erico Marlon Moraes Flores -- 2. Advanced statistical tools and machine learning applied to elemental analysis associated with medical conditions / George L. Donati -- 3. ICP-MS as a tool to understand trace element homeostasis in neurological disorders / Jemmyson Romário de Jesus, Edileuza Marcelo Vieira, Jéssica Passos de Carvalho, and Lucas Hestevan Malta Alfredo -- 4. Biomedical analysis by ICP-MS: a focus on single cell strategies / Maria Montes-Bayón, Mario Corte-Rodríguez, Roberto Álvarez-Fernández García, and Juliana Severo Fagundes -- 5. Exploring ICP-MS as a versatile technique: from imaging to chemical speciation analysis / Renata Stábile Amais, Aline Martins de Andrade, Ana Beatriz Santos da Silva, Daniel Carneiro Freitas, Danielle da Silva Francischini, Alan James Stewart, and Marco Aurélio Zezzi Arruda.
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