DEVELOPMENT AND VALIDATION OF A MIRNA-BASED SIGNATURE, POWERED BY MACHINE LEARNING, FOR PREDICTING 5-YEAR DISEASEFREE SURVIVAL AFTER SURGERY IN EARLY-ONSET COLORECTAL CANCER

被引:0
|
作者
Mannucci, Alessandro
Hernandez, Goretti
Uetake, Hiroyuki
Yamada, Yasuhide
Balaguer, Francesc
Baba, Hideo
Perea, Jose
Boland, Clement R.
Quintero, Enrique
Goel, Ajay
机构
关键词
D O I
暂无
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
1256
引用
收藏
页码:S296 / S297
页数:2
相关论文
共 50 条
  • [42] MACHINE LEARNING-BASED EXPLANATION OF RACIAL-ETHNIC DISPARITIES IN 5-YEAR CANCER-SPECIFIC SURVIVAL AMONG HORMONE RECEPTOR-POSITIVE BREAST CANCER PATIENTS IN THE UNITED STATES
    Harun, R.
    Kim, E.
    Cheng, A.
    Abbass, I
    VALUE IN HEALTH, 2023, 26 (06) : S26 - S26
  • [43] Assessment of co-medication quality in older colorectal cancer patients at hospital discharge after tumor surgery and its associations with chemotherapy-related adverse drug reactions and 5-year survival
    Chen, Li-Ju
    Schoettker, Ben
    PHARMACOEPIDEMIOLOGY AND DRUG SAFETY, 2021, 30 : 75 - 76
  • [44] Development and validation of machine learning models for predicting no. 253 lymph node metastasis in left-sided colorectal cancer using clinical and CT-based radiomic features
    Hongwei Zhang
    Kexin Wang
    Shurong Liu
    Guowei Chen
    Yong Jiang
    Yingchao Wu
    Xiaocong Pang
    Xiaoying Wang
    Junling Zhang
    Xin Wang
    Cancer Imaging, 25 (1)
  • [45] 5-YEAR SURVIVAL OF NON-SMALL CELL LUNG CANCER PATIENTS AFTER RADICAL SURGERY SIGNIFICANTLY DEPENDED ON PHASE TRANSITION "EARLY-INVASIVE CANCER", LYMPH NODE METASTASES AND CELL RATIO FACTORS
    Kshivets, Oleg
    JOURNAL OF THORACIC ONCOLOGY, 2011, 6 (06) : S860 - S861
  • [46] Development and Validation of Deep Learning Model Based on CT Simulator Images to Predict 5-Year Recurrence of Stage IIIA-N2 Non-Small-Cell Lung Cancer Patients Treated with Surgery and Postoperative Radiotherapy
    Ma, Z.
    Yongxing, B.
    Yuan, M.
    Yang, X.
    Zhao, M.
    Shuang, S.
    Sun, X.
    Men, Y.
    Hui, Z.
    INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2021, 111 (03): : E114 - E114
  • [47] Development of Artificial Intelligence-based Machine Learning Models for Predicting Survival In Hormone-Receptor-Positive/HER2-Negative Early Breast Cancer undergoing Neoadjuvant Chemotherapy
    Mastrantoni, Luca
    Garufi, Giovanna
    Maliziola, Noemi
    Di Monte, Elena
    Arcuri, Giorgia
    Frescura, Valentina
    Rotondi, Angelachiara
    Giordano, Giulia
    Carbognin, Luisa
    Fabi, Alessandra
    Paris, Ida
    Franceschini, Gianluca
    Orlandi, Armando
    Palazzo, Antonella
    Scambia, Giovanni
    Tortora, Giampaolo
    Bria, Emilio
    CANCER RESEARCH, 2024, 84 (09)
  • [48] Development and external validation of a novel nomogram for predicting cancer-specific survival in patients with ascending colon adenocarcinoma after surgery: a population-based study (vol 20, pg 126, 2022)
    Zhang, Yi Fan
    Ma, Cheng
    Qian, Xiao Ping
    WORLD JOURNAL OF SURGICAL ONCOLOGY, 2025, 23 (01)
  • [49] Development and validation of nomograms based on pre-/post-operative CEA and CA19-9 for survival predicting in stage I-III colorectal cancer patients after radical resection
    Dai, Xuan
    Li, Yifan
    Wang, Haoran
    Dai, Zhujiang
    Chen, Yuanyuan
    Liu, Yun
    Huang, Shiyong
    FRONTIERS IN ONCOLOGY, 2024, 14
  • [50] An XGBoost Machine Learning Based Model for Predicting Ki-67 Value ≥ 15% in T2NXM0 Stage Primary Breast Cancer Receiving Neoadjuvant Chemotherapy Using Clinical Data and Delta-Radiomic Features on Ultrasound Images and Overall Survival Analysis: A 5-Year Postoperative Follow-Up Study
    Lu, Yang
    Yang, Fei
    Tao, Yichao
    An, Pang
    TECHNOLOGY IN CANCER RESEARCH & TREATMENT, 2024, 23