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2023 연구성과별 연구자 정보 (1547 / 2675)

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Document Title Author Full Name Author Short Name Index Corresponding Address ResearcherID ResearcherID Author Name ORCID ORCID Author Name Related Email
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Kim, Hyeonseon Kim, H 3
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Gennaro, Nicolo Gennaro, N 4 P-1776-2019 Gennaro, Nicolò
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Soliman, Moataz Soliman, M 5
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Kim, Leeseul Kim, L 6
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Oh, Youjin Oh, Y 7
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Djunadi, Trie Arni Djunadi, TA 8
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Lee, Jeeyeon Lee, J 9
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Chung, Liam Il-Young Chung, LIY 10 IQU-0821-2023 Chung, Liam Il-Young
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Yoon, Sung Mi Yoon, SM 11
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Shah, Zunairah Shah, Z 12
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Yang, Won Jun Yang, WJ 13
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Kim, Hye Sung Kim, HS 14 LQV-0440-2024 Kim, Hye Sung
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Lee, Yunjoo Lee, Y 15
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Lee, Soowon Lee, S 16
Machine learning models based on radiomics features to predict treatment response, biomarker status, and bone metastasis in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors (ICIs) Kang, Daeun Kang, D 17
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