A Combined Machine Learning Model for Predicting Pneumonitis of NSCLC Patients Treated with SBRT

被引：0
|
作者：
Halder, K. [1 ]
Podder, T. K. [2 ]
Maria-Joseph, F. [1 ]
Zheng, Y. [3 ]
Mix, M. D. [2 ]
Biswas, T. [4 ]
机构：
[1] Indian Inst Technol, Roorkee, Uttar Pradesh, India
[2] SUNY Upstate Med Univ, Syracuse, NY 13210 USA
[3] Case Western Reserve Univ, Univ Hosp, Cleveland, OH 44106 USA
[4] Case Western Reserve Univ, Metro Hlth, Cleveland, OH 44106 USA
来源：
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS | 2024年 / 120卷 / 02期
关键词：
D O I：
暂无
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
2120
引用
收藏
页码：E56 / E56
页数：1
相关论文
共 50 条
  • [31] Machine Learning Model for Predicting Epidemics
    Bokonda, Patrick Loola
    Sidibe, Moussa
    Souissi, Nissrine
    Ouazzani-Touhami, Khadija
    COMPUTERS, 2023, 12 (03)
  • [32] Predicting combined tidal and pluvial flood inundation using a machine learning surrogate model
    Zahura, Faria T.
    Goodall, Jonathan L.
    JOURNAL OF HYDROLOGY-REGIONAL STUDIES, 2022, 41
  • [33] Machine-learning model for predicting oliguria in critically ill patients
    Yamao, Yasuo
    Oami, Takehiko
    Yamabe, Jun
    Takahashi, Nozomi
    Nakada, Taka-aki
    SCIENTIFIC REPORTS, 2024, 14 (01)
  • [34] Machine-learning model for predicting oliguria in critically ill patients
    Yasuo Yamao
    Takehiko Oami
    Jun Yamabe
    Nozomi Takahashi
    Taka-aki Nakada
    Scientific Reports, 14
  • [35] Machine Learning Model for Predicting Postoperative Survival of Patients with Colorectal Cancer
    Osman, Mohamed Hosny
    Mohamed, Reham Hosny
    Sarhan, Hossam Mohamed
    Park, Eun Jung
    Baik, Seung Hyuk
    Lee, Kang Young
    Kang, Jeonghyun
    CANCER RESEARCH AND TREATMENT, 2022, 54 (02): : 517 - 524
  • [36] IDENTIFYING IMPORTANT CLINICAL FEATURES FOR PREDICTING REMISSION IN PATIENTS WITH RHEUMATOID ARTHRITIS TREATED WITH BIOLOGICS USING MACHINE LEARNING MODEL
    Alsaber, A.
    Al-Herz, A.
    Alawadhi, B.
    Setiya, P.
    Saleh, K.
    Al-Awadhi, A.
    Al-Kandari, W.
    Hasan, E.
    Mokaddem, K.
    Ghanem, A.
    Bartella, Y.
    Hussein, M.
    Alhadhood, N.
    Ali, Y.
    Nahar, E.
    Aldei, A.
    Alenizi, A.
    Hayat, S. H. M.
    Abutiban, F.
    Behbehani, H.
    ANNALS OF THE RHEUMATIC DISEASES, 2023, 82 : 567 - 567
  • [37] Identifying Important Clinical Features for Predicting Remission in Patients with Rheumatoid Arthritis Treated with Biologics Using Machine Learning Model
    Alsaber, Ahmad
    AlHerz, Adeeba
    Alawadhi, Balqees
    Setiya, Parul
    Mohammed, Khuloud
    Al-Awadhi, Adel
    Al-Kandari, Waleed
    Hasan, Eman
    Mokaddem, Khaled
    Ghanem, Aqeel
    Bartella, Youssef
    Hussain, Mohammed
    Alhadhood, Naser
    Ali, Yaser
    Nahar, Ebrahim
    Aldei, Ali
    Alenizi, Ahmad
    Hayat, Sawsan
    Abutiban, Fatemah
    Abutiban, Fatemah
    ARTHRITIS & RHEUMATOLOGY, 2023, 75 : 1923 - 1926
  • [38] Predicting Serum Levels of Lithium-Treated Patients: A Supervised Machine Learning Approach
    Hsu, Chih-Wei
    Tsai, Shang-Ying
    Wang, Liang-Jen
    Liang, Chih-Sung
    Carvalho, Andre F.
    Solmi, Marco
    Vieta, Eduard
    Lin, Pao-Yen
    Hu, Chien-An
    Kao, Hung-Yu
    BIOMEDICINES, 2021, 9 (11)
  • [39] Three Definitions of Normal Lung Volumes for Predicting Radiation Pneumonitis in Advanced NSCLC Treated With Radical Chemoradiation Therapy
    Chen, Z.
    Xie, S.
    Xu, Z.
    Liang, Y.
    Pan, Y.
    JOURNAL OF THORACIC ONCOLOGY, 2021, 16 (03) : S261 - S261
  • [40] Machine learning based on blood biomarkers predicts fast progression in advanced NSCLC patients treated with immunotherapy
    Zhou, J-G.
    Yang, J.
    Wang, H.
    Wong, A. H-H.
    Tan, F.
    Chen, X.
    He, S.
    Shen, G.
    Wang, Y-J.
    Frey, B.
    Fietkau, R.
    Hecht, M.
    Ma, H.
    Gaipl, U. S.
    ANNALS OF ONCOLOGY, 2022, 33 : S59 - S59
12345