Machine Learning Nomogram to Predict Breast Reconstruction Complications with and without Radiation

被引:0
|
作者
Naoum, G. E. [1 ]
Ho, A. Y. [2 ]
Salama, L. W. [3 ]
Shui, A. M. [2 ]
Taghian, A. G. [4 ,5 ]
机构
[1] Harvard Med Sch, Dept Radiat Oncol, Massachusetts Gen Hosp, Boston, MA 02115 USA
[2] Massachusetts Gen Hosp, Boston, MA 02114 USA
[3] Charles E Schmidt COM FAU, Boca Raton, FL USA
[4] Massachusetts Gen Hosp, Dept Radiat Oncol, Boston, MA 02114 USA
[5] Harvard Med Sch, Boston, MA 02115 USA
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
2045
引用
收藏
页码:E20 / E20
页数:1
相关论文
共 50 条
  • [1] Risk of Developing Breast Reconstruction Complications: A Machine-Learning Nomogram for Individualized Risk Estimation with and without Postmastectomy Radiation Therapy
    Naoum, George E.
    Ho, Alice Y.
    Shui, Amy
    Salama, Laura
    Goldberg, Saveli
    Arafat, Waleed
    Winograd, Jonathan
    Colwell, Amy
    Smith, Barbara L.
    Taghian, Alphonse G.
    [J]. PLASTIC AND RECONSTRUCTIVE SURGERY, 2022, 149 (01) : 1E - 12E
  • [2] Predicting Complications in Breast Reconstruction Development and Prospective Validation of a Machine Learning Model
    Braun, Sterling E.
    Sinik, Lauren M.
    Meyer, Anne M.
    Larson, Kelsey E.
    Butterworth, James A.
    [J]. ANNALS OF PLASTIC SURGERY, 2023, 91 (02) : 282 - 286
  • [3] Machine Learning to Predict the Need for Postmastectomy Radiotherapy after Immediate Breast Reconstruction
    Chen, Yi-Fu
    Chawla, Sahil
    Mousa-Doust, Dorsa
    Nichol, Alan
    Ng, Raymond
    Isaac, Kathryn V.
    [J]. PLASTIC AND RECONSTRUCTIVE SURGERY-GLOBAL OPEN, 2024, 12 (02) : E5599
  • [4] Tissue Expander/Implant Breast Reconstruction with and without Postmastectomy Radiation: Predictive Factors for Complications
    Nguyen, S. K. A.
    Oxley, P.
    Rastegar, R.
    Joffres, M.
    Kwan, W.
    [J]. CANCER RESEARCH, 2012, 72
  • [5] MACHINE LEARNING POSSIBILITIES TO PREDICT SEVERE OBSTETRIC COMPLICATIONS
    Ivshin, Aleksandr a.
    Boldina, Yuliia s.
    Svetova, Kristina s.
    Shtykov, Aleksey s.
    Vasilev, Aleksey s.
    [J]. AD ALTA-JOURNAL OF INTERDISCIPLINARY RESEARCH, 2023, 13 (02): : 319 - 325
  • [6] Tissue Expander Complications Predict Permanent Implant Complications and Failure of Breast Reconstruction
    Huang, Jiuzuo
    Yu, Nanze
    Long, Xiao
    [J]. ANNALS OF PLASTIC SURGERY, 2016, 76 (02) : 259 - 259
  • [7] Tissue Expander Complications Predict Permanent Implant Complications and Failure of Breast Reconstruction
    Adkinson, Joshua M.
    Miller, Nathan F.
    Eid, Sherrine M.
    Miles, Marshall G.
    Murphy, Robert X., Jr.
    [J]. ANNALS OF PLASTIC SURGERY, 2015, 75 (01) : 24 - 28
  • [8] impact of breast radiation therapy on complications after alloplastic breast reconstruction
    Chaves, C. D. L. G.
    Carvalho, H. D. A.
    Saraiva, T. D. C.
    Fuzisaki, T. T.
    Marta, G. N.
    Casagrande, R.
    Munhoz, A.
    Brasil, J. A.
    Stuart, S. R.
    [J]. RADIOTHERAPY AND ONCOLOGY, 2017, 123 : S343 - S344
  • [9] Applying a Machine Learning Approach to Predict Acute Toxicities During Radiation for Breast Cancer Patients
    Reddy, J.
    Lindsay, W. D.
    Berlind, C. G.
    Ahern, C. A.
    Smith, B. D.
    [J]. INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS, 2018, 102 (03): : S59 - S59
  • [10] Development and validation of a nomogram to predict impacted ureteral stones via machine learning
    Qi, Yuanjiong
    Yang, Shushuai
    Li, Jingxian
    Xing, Haonan
    Su, Qiang
    Wang, Siyuan
    Chen, Yue
    Qi, Shiyong
    [J]. MINERVA UROLOGY AND NEPHROLOGY, 2024,