Machine Learning Predictability of Clinical Next Generation Sequencing for Hematologic Malignancies to Guide High-Value Precision Medicine.

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第一作者： Grace Y E,Kim

第一单位： Department of Computer Science, Stanford, CA.

作者： Grace Y E,Kim ^[1] ; Morteza,Noshad ^[2] ; Henning,Stehr ^[3] ; Rebecca,Rojansky ^[3] ; Dita,Gratzinger ^[3] ; Jean,Oak ^[3] ; Rondeep,Brar ^[4] ; David,Iberri ^[4] ; Christina,Kong ^[3] ; James,Zehnder ^[3] ; Jonathan H,Chen ^[4]

作者单位： Department of Computer Science, Stanford, CA. ^[1] Stanford Center for Biomedical Informatics Research, Stanford, CA. ^[2] Department of Pathology, Stanford, CA. ^[3] Department of Hematology, Stanford, CA. ^[4] Division of Hospital Medicine, Stanford, CA. ^[5]

主题词血液肿瘤(Hematologic Neoplasms);血红素(Heme);高通量核苷酸序列分析(High-Throughput Nucleotide Sequencing);人类(Humans);突变(Mutation)

PMID 35308914

发布时间 2024-05-11

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AMIA ... Annual Symposium proceedings. AMIA Symposium

2021年2021卷

641-650页

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Machine Learning Predictability of Clinical Next Generation Sequencing for Hematologic Malignancies to Guide High-Value Precision Medicine.

AMIA ... Annual Symposium proceedings. AMIA Symposium

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AMIA ... Annual Symposium proceedings. AMIA Symposium

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Machine Learning Predictability of Clinical Next Generation Sequencing for Hematologic Malignancies to Guide High-Value Precision Medicine.

AMIA ... Annual Symposium proceedings. AMIA Symposium

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AMIA ... Annual Symposium proceedings. AMIA Symposium

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