Using the 'Routes from Diagnosis' framework to understand variations in survivorship outcomes for Breast Cancer in the City of Manchester

被引：0
|
作者：
Chapman, David [1 ]
Ulmann, George [1 ]
Standing, Mike [1 ]
Flynn, Julie [2 ]
Cook, Nicola [2 ]
Woolmore, Ashley [3 ]
Makin, Wendy [4 ]
Bunfred, Nigel [5 ]
机构：
[1] Monitor Deloitte, London, England
[2] Macmillan Canc Support, London, England
[3] IMS Hlth, London, England
[4] Christie Hosp NHS FT, Manchester, Lancs, England
[5] Univ Hosp South Manchester NHS FT, Manchester, Lancs, England
来源：
EUROPEAN JOURNAL OF CANCER CARE | 2015年 / 24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：
P-92
引用
收藏
页码：57 / 57
页数：1
相关论文
共 50 条
  • [41] Automated diagnosis of breast cancer from ultrasound images using diverse ML techniques
    R. Karthiga
    K. Narasimhan
    [J]. Multimedia Tools and Applications, 2022, 81 : 30169 - 30193
  • [42] Interpretable Diagnosis of Breast Cancer from Histological Images Using Siamese Neural Networks
    Hradel, Dominik
    Hudec, Lukas
    Benesova, Wanda
    [J]. TWELFTH INTERNATIONAL CONFERENCE ON MACHINE VISION (ICMV 2019), 2020, 11433
  • [43] Automated diagnosis of breast cancer from ultrasound images using diverse ML techniques
    Karthiga, R.
    Narasimhan, K.
    [J]. MULTIMEDIA TOOLS AND APPLICATIONS, 2022, 81 (21) : 30169 - 30193
  • [44] Chemometrics assisted investigation of variations in infrared spectra of blood samples obtained from women with breast cancer: a new approach for cancer diagnosis
    Khanmohammadi, M.
    Rajabi, F. H.
    Garmarudi, A. B.
    Mohammadzadeh, R.
    Mohammadzadeh, R.
    [J]. EUROPEAN JOURNAL OF CANCER CARE, 2010, 19 (03) : 352 - 359
  • [45] Feasibility of using data from the All of Us Research Program to better understand Asian American breast cancer risk
    Garcia, Catalina Haas
    Chen, Wen-Pin
    Liu, Danni
    Lee, Alice W.
    Zhang, Min
    Ziogas, Argyrios
    Tanjasiri, Sora
    Park, Hannah Lui
    [J]. CANCER EPIDEMIOLOGY BIOMARKERS & PREVENTION, 2024, 33 (09)
  • [46] Enhancing early breast cancer diagnosis through automated microcalcification detection using an optimized ensemble deep learning framework
    Teoh, Jing Ru
    Hasikin, Khairunnisa
    Lai, Khin Wee
    Wu, Xiang
    Li, Chong
    [J]. PEERJ COMPUTER SCIENCE, 2024, 10
  • [47] Enhancing early breast cancer diagnosis through automated microcalcification detection using an optimized ensemble deep learning framework
    Teoh, Jing Ru
    Hasikin, Khairunnisa
    Lai, Khin Wee
    Wu, Xiang
    Li, Chong
    [J]. PeerJ Computer Science, 2024, 10
  • [48] Improving Breast Cancer Detection and Diagnosis through Semantic Segmentation Using the Unet3+ Deep Learning Framework
    Alam, Taukir
    Shia, Wei-Chung
    Hsu, Fang-Rong
    Hassan, Taimoor
    [J]. BIOMEDICINES, 2023, 11 (06)
  • [49] Biological subtype, treatment response and outcomes in inflammatory breast cancer using data from the National Cancer Database
    Kupstas, A. R.
    Hoskin, T. L.
    Day, C. N.
    Boughey, J. C.
    Habermann, E. B.
    Hieken, T. J.
    [J]. BRITISH JOURNAL OF SURGERY, 2020, 107 (08) : 1033 - 1041
  • [50] Computer-Aided Breast Cancer Diagnosis from Thermal Images Using Transfer Learning
    Cabioglu, Cagri
    Ogul, Hasan
    [J]. BIOINFORMATICS AND BIOMEDICAL ENGINEERING (IWBBIO 2020), 2020, 12108 : 716 - 726
12345