IDENTIFYING PREDICTIVE FACTORS FOR LOSS TO FOLLOW UP IN PEDIATRIC BONE MARROW TRANSPLANTATION PATIENTS USING SUPERVISED MACHINE LEARNING

被引：0
|
作者：
Nagy, Matthew [1 ]
Rotz, Seth [1 ]
机构：
[1] Cleveland Clin Childrens, Cleveland, OH USA
来源：
PEDIATRIC BLOOD & CANCER | 2021年 / 68卷
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：
引用
收藏
页码：S201 / S201
页数：1
相关论文
共 50 条
  • [1] A supervised machine learning model for identifying predictive factors for recommending head and neck cancer surgery
    Jiam, Max L.
    Xin, Kevin Z.
    Ha, Patrick K.
    Jiam, Nicole T.
    HEAD AND NECK-JOURNAL FOR THE SCIENCES AND SPECIALTIES OF THE HEAD AND NECK, 2024, 46 (05): : 1001 - 1008
  • [2] MOLECULAR FOLLOW-UP OF PATIENTS AFTER BONE-MARROW TRANSPLANTATION
    BRDICKA, R
    SIEGLOVA, Z
    PISACKA, M
    HRABANEK, J
    LOUDOVA, M
    HASKOVEC, C
    STEM CELLS, 1993, 11 : 42 - 45
  • [3] MODELING MORTALITY OF PEDIATRIC PATIENTS UNDERGOING HEMATOPOIETIC STEM CELL TRANSPLANTATION USING SUPERVISED MACHINE LEARNING
    Dunn, A.
    Cao, A.
    Gobburu, J.
    Long-Boyle, J.
    Goyal, R.
    CLINICAL PHARMACOLOGY & THERAPEUTICS, 2023, 113 : S65 - S65
  • [4] PSYCHOSOCIAL PREPARATION AND FOLLOW-UP FOR PEDIATRIC BONE-MARROW TRANSPLANT PATIENTS
    ATKINS, DM
    PATENAUDE, AF
    AMERICAN JOURNAL OF ORTHOPSYCHIATRY, 1987, 57 (02) : 246 - 252
  • [5] Follow-up of nine patients with Hurler syndrome after bone marrow transplantation
    Guffon, N
    Souillet, G
    Maire, I
    Straczek, J
    Guibaud, P
    JOURNAL OF PEDIATRICS, 1998, 133 (01): : 119 - 125
  • [6] LONG-TERM FOLLOW-UP OF PEDIATRIC PATIENTS RECEIVING TOTAL BODY IRRADIATION BEFORE BONE MARROW TRANSPLANTATION
    Knenkele, Annette
    Engelhard, Marianne
    Hauffa, Berthold
    Mellies, Uwe
    Schulte, Johannes
    Eggert, Angelika
    Huer, Claudia
    Kremens, Bernhard
    PEDIATRIC BLOOD & CANCER, 2011, 57 (05) : 827 - 827
  • [7] Prevalence of Gastroparesis in Patients With Chronic Pancreatitis and Predictive Factors: A Novel Prediction Model Using Supervised Machine Learning
    Ramai, Daryl
    Pan, Chun-Wei
    Fellows, Emily
    Wang, Yichen
    Huang, Yuting
    Shah, Ishani
    Simsek, Cem
    Spadaccini, Marco
    Maida, Marcello
    Chandan, Saurabh
    Facciorusso, Antonio
    Troendle, David
    Machicado, Jorge D.
    AMERICAN JOURNAL OF GASTROENTEROLOGY, 2024, 119 (10S): : S74 - S74
  • [8] Supervised Machine Learning to Predict Follow-Up Among Adjuvant Endocrine Therapy Patients
    Harrell, Morgan
    Levy, Mia
    Fabbri, Daniel
    2017 IEEE INTERNATIONAL CONFERENCE ON HEALTHCARE INFORMATICS (ICHI), 2017, : 490 - 495
  • [9] Identifying Risk Factors and Predicting Food Security Status using Supervised Machine Learning Techniques
    Alelign, Melaku
    Abuhay, Tesfamariam M.
    Letta, Adane
    Dereje, Tizita
    2021 INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION TECHNOLOGY FOR DEVELOPMENT FOR AFRICA (ICT4DA), 2021, : 12 - 17
  • [10] ONE YEAR FOLLOW UP OF ORAL CONDITION IN PATIENTS TREATED WITH BONE-MARROW TRANSPLANTATION
    HEIMDAHL, A
    JOHNSON, G
    JOURNAL OF DENTAL RESEARCH, 1985, 64 (04) : 766 - 766
12345