Improving pancreatic cancer image classification with transfer learning: CD45 vs. PANCK

被引：0
|
作者：
Thomas, Miracle
机构：
来源：
CANCER RESEARCH | 2024年 / 84卷 / 22期
关键词：
D O I：
10.1158/1538-7445.TUMBODY-B010
中图分类号：
R73 [肿瘤学];
学科分类号：
100214 ;
摘要：
B010
引用
收藏
页数：2
相关论文
共 42 条
  • [21] Machine learning improves classification of preclinical models of pancreatic cancer with chemical exchange saturation transfer MRI
    Goldenberg, Joshua M.
    Cardenas-Rodriguez, Julio
    Pagel, Mark D.
    MAGNETIC RESONANCE IN MEDICINE, 2019, 81 (01) : 594 - 601
  • [22] Deep Learning for Semantic Segmentation vs. Classification in Computational Pathology: Application to Mitosis Analysis in Breast Cancer Grading
    Jimenez, Gabriel
    Racoceanu, Daniel
    FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY, 2019, 7 (JUN)
  • [23] The development of an efficient artificial intelligence-based classification approach for colorectal cancer response to radiochemotherapy: deep learning vs. machine learning
    Bahrambanan, Fatemeh
    Alizamir, Meysam
    Moradveisi, Kayhan
    Heddam, Salim
    Kim, Sungwon
    Kim, Seunghyun
    Soleimani, Meysam
    Afshar, Saeid
    Taherkhani, Amir
    SCIENTIFIC REPORTS, 2025, 15 (01):
  • [24] Sparrow Search Algorithm With Stacked Deep Learning Based Medical Image Analysis for Pancreatic Cancer Detection and Classification
    Ramesh, Janjhyam Venkata Naga
    Abirami, T.
    Gopalakrishnan, T.
    Narayanasamy, Kanagaraj
    Ishak, Mohamad Khairi
    Karim, Faten Khalid
    Mostafa, Samih M.
    Allakany, Alaa
    IEEE ACCESS, 2023, 11 : 111927 - 111935
  • [25] Galactic swarm optimization with deep transfer learning driven colorectal cancer classification for image guided intervention
    Escorcia-Gutierrez, Jose
    Gamarra, Margarita
    Ariza-Colpas, Paola Patricia
    Roncallo, Gisella Borja
    Leal, Nallig
    Soto-Diaz, Roosvel
    Mansour, Romany F.
    COMPUTERS & ELECTRICAL ENGINEERING, 2022, 104
  • [26] Galactic swarm optimization with deep transfer learning driven colorectal cancer classification for image guided intervention
    Escorcia-Gutierrez, José
    Gamarra, Margarita
    Ariza-Colpas, Paola Patricia
    Roncallo, Gisella Borja
    Leal, Nallig
    Soto-Diaz, Roosvel
    Mansour, Romany F.
    Computers and Electrical Engineering, 2022, 104
  • [27] Integrating expert guidance with gradual moment approximation (GMAp)-enhanced transfer learning for improved pancreatic cancer classification
    Jasmine Chhikara
    Nidhi Goel
    Neeru Rathee
    Neural Computing and Applications, 2025, 37 (3) : 1357 - 1373
  • [28] Optimization of automated tissue classification in histopathological images: use of a deep transfer learning approach on a pancreatic cancer cohort
    Haeberle, L.
    Kronberg, R.
    Pfaus, M.
    Xu, H.
    Krings, K.
    Schlensog, M.
    Rau, T.
    Pandyra, A.
    Lang, K.
    Esposito, I.
    Lang, P.
    VIRCHOWS ARCHIV, 2022, 481 (SUPPL 1) : S79 - S79
  • [29] Enhancing breast cancer classification via histopathological image analysis: Leveraging self-supervised contrastive learning and transfer learning
    Bin Ashraf, Faisal
    Alam, S. M. Maksudul
    Sakib, Shahriar M.
    HELIYON, 2024, 10 (02)
  • [30] BTLA+CD200+ B cells dictate the divergent immune landscape and immunotherapeutic resistance in metastatic vs. primary pancreatic cancer
    Brian Diskin
    Salma Adam
    Gustavo Sanchez Soto
    Miguel Liria
    Berk Aykut
    Belen Sundberg
    Eric Li
    Joshua Leinwand
    Ruonan Chen
    Mirhee Kim
    Ruben D. Salas
    Marcelo F. Cassini
    Chandan Buttar
    Wei Wang
    Mohammad Saad Farooq
    Sorin A. A. Shadaloey
    Gregor Werba
    Amreek Fnu
    Fan Yang
    Carolina Hirsch
    John Glinski
    Angilee Panjwani
    Yael Weitzner
    Deirdre Cohen
    Usman Asghar
    George Miller
    Oncogene, 2022, 41 : 4349 - 4360
12345