EVALUATION OF REAL-WORLD RESPONSE RATE IN CLINICAL TRIAL-ALIGNED COHORTS OF PATIENTS WITH LUNG, COLON, AND BREAST CANCER USING MACHINE LEARNING

被引：0
|
作者：
Zhang, Q. [1 ]
Krismer, K. [2 ]
Wang, X. [2 ]
Fullerton, C. [2 ]
Dolor, A. [2 ]
Wade, N. B. [2 ]
Baruah, P. [2 ]
Yim, E. [2 ]
Williams, T. [2 ]
Yuan, Q. [2 ]
Wilkinson, S. [2 ]
Nemeth, S. [2 ]
Singh, N. [2 ]
Wang, M. [2 ]
Richey, M. [2 ]
Cohen, A. B. [2 ]
Fidyk, E. [2 ]
Blarre, A. [2 ]
Magee, K. [2 ]
机构：
[1] Flatiron Hlth, Jersey City, NJ USA
[2] Flatiron Hlth, New York, NY USA
来源：
VALUE IN HEALTH | 2024年 / 27卷 / 06期
关键词：
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
MSR79
引用
收藏
页码：S274 / S274
页数：1
相关论文
共 50 条
  • [21] Predicting recurrence of venous thromboembolism in anticoagulated cancer patients using real-world data and machine learning.
    Martin, Andres J. Munoz
    Dominguez, Sofia Huerga
    Souto, Juan Carlos
    Revuelta, Jacobo Rogado
    Sanchez, Antonio
    Garcia-Palomo, Andres
    Aparicio, Jorge
    Aguayo, Cristina
    Abad, David Gutierrez
    Ortega, Laura
    Vinuela-Beneitez, Maria Carmen
    Fanjul, Victor
    Casadevall, David
    Arumi, Daniel
    Hernandez-Presa, Miguel Angel
    JOURNAL OF CLINICAL ONCOLOGY, 2022, 40 (16) : E18742 - E18742
  • [22] An application of machine learning based on real-world data: Mining features of fibrinogen in clinical stages of lung cancer between sexes
    Yin, Fangtao
    Zhu, Hongyu
    Hong, Songlin
    Sun, Chen
    Wang, Jie
    Sun, Mengting
    Xu, Lin
    Wang, Xiaoxiao
    Yin, Rong
    ANNALS OF TRANSLATIONAL MEDICINE, 2021, 9 (08)
  • [23] Eligibility of real-world patients with metastatic lung cancer for clinical trial participation: A population-based analysis.
    Batra, Atul
    Kong, Shiying
    Rigo, Rodrigo
    Cheung, Winson Y.
    JOURNAL OF CLINICAL ONCOLOGY, 2020, 38 (29)
  • [24] Enhancing the utilization of deep learning to predict patient response in small immunotherapy cohorts using real-world data
    Arango-Argoty, Gustavo
    Jacob, Etai
    CANCER RESEARCH, 2023, 83 (07)
  • [25] ctDNA and Real-World Response (rwR) in Patients With Lung Cancer From A Prospective Real-World Clinico-Genomic (PCG) Study
    Vanderwalde, A.
    Lu, M.
    Maund, S.
    Huntley, M.
    Incerti, D.
    Fine, A.
    Tolba, K.
    Jin, D.
    Bourla, A.
    Sondhi, A.
    Tromanhauser, M.
    Daniel, D.
    Tilford, J.
    Mcfarlane, J.
    Lakhanpal, S.
    Oxnard, G.
    Schulze, K.
    JOURNAL OF THORACIC ONCOLOGY, 2021, 16 (10) : S1005 - S1005
  • [26] Automatic body part identification in real-world clinical dermatological images using machine learning
    Sitaru, Sebastian
    Oueslati, Talel
    Schielein, Maximilian C.
    Weis, Johanna
    Kaczmarczyk, Robert
    Rueckert, Daniel
    Biedermann, Tilo
    Zink, Alexander
    JOURNAL DER DEUTSCHEN DERMATOLOGISCHEN GESELLSCHAFT, 2023, 21 (08): : 863 - 869
  • [27] Comparing Trial and Real-world Adjuvant Oxaliplatin Delivery in Patients With Stage III Colon Cancer Using a Longitudinal Cumulative Dose
    Webster-Clark, Michael
    Keil, Alexander P.
    Robert, Nicholas
    Frytak, Jennifer R.
    Boyd, Marley
    Sturmer, Til
    Sanoff, Hanna
    Westreich, Daniel
    Lund, Jennifer L.
    JAMA ONCOLOGY, 2022, 8 (12) : 1821 - 1824
  • [28] A novel analytical framework for risk stratification of real-world data using machine learning: A small cell lung cancer study
    Marzano, Luca
    Darwich, Adam S.
    Tendler, Salomon
    Dan, Asaf
    Lewensohn, Rolf
    De Petris, Luigi
    Raghothama, Jayanth
    Meijer, Sebastiaan
    CTS-CLINICAL AND TRANSLATIONAL SCIENCE, 2022, 15 (10): : 2437 - 2447
  • [29] Feasibility and User Experience of Digital Patient Monitoring for Real-World Patients With Lung or Breast Cancer
    Arriola, Edurne
    Jaal, Jana
    Edvardsen, Anne
    Silvoniemi, Maria
    Araujo, Antonio
    Vikstrom, Anders
    Zairi, Eleni
    Rodriguez-Mues, Mari Carmen
    Roccato, Marco
    Schneider, Sophie
    Ammann, Johannes
    ONCOLOGIST, 2024, 29 (04): : e561 - e569
  • [30] Comparison of real-world response rate (rwRR) to RECIST-based response rate in patients with advanced non-small cell lung cancer (aNSCLC)
    Ma, X.
    Nussbaum, N. C.
    Magee, K.
    Bourla, A. B.
    Tucker, M.
    Bellomo, L.
    Bennette, C.
    ANNALS OF ONCOLOGY, 2019, 30
12345