Enhancing Lung Cancer Classification through Integration of Liquid Biopsy Multi-Omics Data with Machine Learning Techniques.

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第一作者： Hyuk-Jung,Kwon

第一单位： Eone-Diagnomics Genome Center, Inc., 143, Gaetbeol-ro, Yeonsu-gu, Incheon 21999, Republic of Korea.

作者： Hyuk-Jung,Kwon ^[1] ; Ui-Hyun,Park ^[2] ; Chul Jun,Goh ^[1] ; Dabin,Park ^[1] ; Yu Gyeong,Lim ^[1] ; Isaac Kise,Lee ^[1] ; Woo-Jung,Do ^[1] ; Kyoung Joo,Lee ^[2] ; Hyojung,Kim ^[3] ; Seon-Young,Yun ^[1] ; Joungsu,Joo ^[1] ; Na Young,Min ^[1] ; Sunghoon,Lee ^[1] ; Sang-Won,Um ^[1] ; Min-Seob,Lee ^[1]

作者单位： Eone-Diagnomics Genome Center, Inc., 143, Gaetbeol-ro, Yeonsu-gu, Incheon 21999, Republic of Korea. ^[1] Department of Computer Science and Engineering, Incheon National University (INU), Incheon 22012, Republic of Korea. ^[2] NGENI Foundation, San Diego, CA 92123, USA. ^[3] Division of Pulmonary and Critical Care Medicine, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, 81 Irwon-ro, Gangnam-gu, Seoul 06351, Republic of Korea. ^[4] Diagnomics, Inc., 5795 Kearny Villa Rd., San Diego, CA 92123, USA. ^[5]

关键词 cell-free DNA copy number variation genomics liquid biopsy lung cancer machine learning multi-omics non-invasive tumor marker

DOI 10.3390/cancers15184556

PMID 37760525

发布时间 2023-10-03

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