Showing 1 - 13 results of 13 for search 'Bum-Sup Jang', query time: 0.05s Refine Results
  1. 1
    Relationship between Macrophage and Radiosensitivity in Human Primary and Recurrent Glioblastoma: In Silico Analysis with Publicly Available Datasets

    Relationship between Macrophage and Radiosensitivity in Human Primary and Recurrent Glioblastoma: In Silico Analysis with Publicly Available Datasets by Bum-Sup Jang, In Ah Kim

    Published 2022-01-01
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  2. 2
    Socioeconomic status and survival outcomes in elderly cancer patients: A national health insurance service‐elderly sample cohort study

    Socioeconomic status and survival outcomes in elderly cancer patients: A national health insurance service‐elderly sample cohort study by Bum‐Sup Jang, Ji Hyun Chang

    Published 2019-07-01
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  3. 3
    Exploration of biomedical knowledge for recurrent glioblastoma using natural language processing deep learning models

    Exploration of biomedical knowledge for recurrent glioblastoma using natural language processing deep learning models by Bum-Sup Jang, Andrew J. Park, In Ah Kim

    Published 2022-10-01
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  4. 4
    Association between gut microbial change and acute gastrointestinal toxicity in patients with prostate cancer receiving definitive radiation therapy

    Association between gut microbial change and acute gastrointestinal toxicity in patients with prostate cancer receiving definitive radiation therapy by Bum‐Sup Jang, Moon Gyu Chung, Dong Soo Lee

    Published 2023-11-01
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  5. 5
    Genomic landscape of locally advanced rectal adenocarcinoma: Comparison between before and after neoadjuvant chemoradiation and effects of genetic biomarkers on clinical outcomes and tumor response

    Genomic landscape of locally advanced rectal adenocarcinoma: Comparison between before and after neoadjuvant chemoradiation and effects of genetic biomarkers on clinical outcomes a... by Tae Hoon Lee, Bum‐Sup Jang, Ji Hyun Chang, Eunji Kim, Jeong Hwan Park, Eui Kyu Chie

    Published 2023-07-01
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  6. 6
    Evaluation of initial patient setup methods for breast cancer between surface-guided radiation therapy and laser alignment based on skin marking in the Halcyon system

    Evaluation of initial patient setup methods for breast cancer between surface-guided radiation therapy and laser alignment based on skin marking in the Halcyon system by Seonghee Kang, Hyeongmin Jin, Ji Hyun Chang, Bum‑Sup Jang, Kyung Hwan Shin, Chang Heon Choi, Jung-in Kim

    Published 2023-04-01
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  7. 7
    Feasibility of anomaly score detected with deep learning in irradiated breast cancer patients with reconstruction

    Feasibility of anomaly score detected with deep learning in irradiated breast cancer patients with reconstruction by Dong-Yun Kim, Soo Jin Lee, Eun Kyu Kim, Eunyoung Kang, Chan Yeong Heo, Jae Hoon Jeong, Yujin Myung, In Ah Kim, Bum-Sup Jang

    Published 2022-08-01
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  8. 8
    Author Correction: Feasibility of anomaly score detected with deep learning in irradiated breast cancer patients with reconstruction

    Author Correction: Feasibility of anomaly score detected with deep learning in irradiated breast cancer patients with reconstruction by Dong-Yun Kim, Soo Jin Lee, Eun-Kyu Kim, Eunyoung Kang, Chan Yeong Heo, Jae Hoon Jeong, Yujin Myung, In Ah Kim, Bum-Sup Jang

    Published 2022-09-01
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  9. 9
    Protocol for the postoperative radiotherapy in N1 breast cancer patients (PORT-N1) trial, a prospective multicenter, randomized, controlled, non-inferiority trial of patients receiving breast-conserving surgery or mastectomy

    Protocol for the postoperative radiotherapy in N1 breast cancer patients (PORT-N1) trial, a prospective multicenter, randomized, controlled, non-inferiority trial of patients recei... by Tae Hoon Lee, Ji Hyun Chang, Bum-Sup Jang, Jae Sik Kim, Tae Hyun Kim, Won Park, Yong Bae Kim, Su Ssan Kim, Wonshik Han, Han-Byoel Lee, Kyung Hwan Shin

    Published 2022-11-01
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  10. 10
    Machine Learning Model to Predict Pseudoprogression Versus Progression in Glioblastoma Using MRI: A Multi-Institutional Study (KROG 18-07)

    Machine Learning Model to Predict Pseudoprogression Versus Progression in Glioblastoma Using MRI: A Multi-Institutional Study (KROG 18-07) by Bum-Sup Jang, Andrew J. Park, Seung Hyuck Jeon, Il Han Kim, Do Hoon Lim, Shin-Hyung Park, Ju Hye Lee, Ji Hyun Chang, Kwan Ho Cho, Jin Hee Kim, Leonard Sunwoo, Seung Hong Choi, In Ah Kim

    Published 2020-09-01
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  11. 11
    Optimizing External Beam Radiotherapy as per the Risk Group of Localized Prostate Cancer: A Nationwide Multi-Institutional Study (KROG 18-15)

    Optimizing External Beam Radiotherapy as per the Risk Group of Localized Prostate Cancer: A Nationwide Multi-Institutional Study (KROG 18-15) by Seo Hee Choi, Young Seok Kim, Jesang Yu, Taek-Keun Nam, Jae-Sung Kim, Bum-Sup Jang, Jin Ho Kim, Youngkyong Kim, Bae Kwon Jeong, Ah Ram Chang, Young-Hee Park, Sung Uk Lee, Kwan Ho Cho, Jin Hee Kim, Hunjung Kim, Youngmin Choi, Yeon Joo Kim, Dong Soo Lee, Young Ju Shin, Su Jung Shim, Won Park, Jaeho Cho

    Published 2021-05-01
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  12. 12
    Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a multi-institutional study

    Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a... by Min Seo Choi, Jee Suk Chang, Kyubo Kim, Jin Hee Kim, Tae Hyung Kim, Sungmin Kim, Hyejung Cha, Oyeon Cho, Jin Hwa Choi, Myungsoo Kim, Juree Kim, Tae Gyu Kim, Seung-Gu Yeo, Ah Ram Chang, Sung-Ja Ahn, Jinhyun Choi, Ki Mun Kang, Jeanny Kwon, Taeryool Koo, Mi Young Kim, Seo Hee Choi, Bae Kwon Jeong, Bum-Sup Jang, In Young Jo, Hyebin Lee, Nalee Kim, Hae Jin Park, Jung Ho Im, Sea-Won Lee, Yeona Cho, Sun Young Lee, Ji Hyun Chang, Jaehee Chun, Eung Man Lee, Jin Sung Kim, Kyung Hwan Shin, Yong Bae Kim

    Published 2024-02-01
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  13. 13
    Corrigendum to ‘Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for RTQA program in a multi-institutional study’ [The Breast 73 (2024) 103599]

    Corrigendum to ‘Assessment of deep learning-based auto-contouring on interobserver consistency in target volume and organs-at-risk delineation for breast cancer: Implications for R... by Min Seo Choi, Jee Suk Chang, Kyubo Kim, Jin Hee Kim, Tae Hyung Kim, Sungmin Kim, Hyejung Cha, Oyeon Cho, Jin Hwa Choi, Myungsoo Kim, Juree Kim, Tae Gyu Kim, Seung-Gu Yeo, Ah Ram Chang, Sung-Ja Ahn, Jinhyun Choi, Ki Mun Kang, Jeanny Kwon, Taeryool Koo, Mi Young Kim, Seo Hee Choi, Bae Kwon Jeong, Bum-Sup Jang, In Young Jo, Hyebin Lee, Nalee Kim, Hae Jin Park, Jung Ho Im, Sea-Won Lee, Yeona Cho, Sun Young Lee, Ji Hyun Chang, Jaehee Chun, Eung Man Lee, Jin Sung Kim, Kyung Hwan Shin, Yong Bae Kim

    Published 2024-04-01
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