Novel deep learning model and validation of whole slide images in lung cancer diagnosis

被引:0
|
作者
Ahmed, A. A. [1 ]
Fawi, M. [2 ]
Brychcy, A. [3 ]
Abouzid, M. [4 ]
Witt, M. [5 ]
Kaczmarek, E. [1 ]
机构
[1] PUMS Poznan Univ Med Sci, Bioinformat & Computat Biol, Poznan, Poland
[2] Spider Silk Secur DMCC, Data Sci, Dubai, U Arab Emirates
[3] Poznan Univ Med Sci, Dept Clin Patomorphol, DeparHeliodor Swiecicki Clin Hosp, Poznan, Poland
[4] PUMS Poznan Univ Med Sci, Dept Phys Pharm & Pharmacokinet, Poznan, Poland
[5] PUMS Poznan Univ Med Sci, Dept Anat, Poznan, Poland
关键词
D O I
10.1016/j.annonc.2024.08.1261
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
1201P
引用
收藏
页码:S772 / S772
页数:1
相关论文
共 50 条
  • [41] Recent developments in cervical cancer diagnosis using deep learning on whole slide images: An Overview of models, techniques, challenges and future directions
    Sambyal, Diksha
    Sarwar, Abid
    MICRON, 2023, 173
  • [42] Deep learning-based histopathological segmentation for whole slide images of colorectal cancer in a compressed domain
    Hyeongsub Kim
    Hongjoon Yoon
    Nishant Thakur
    Gyoyeon Hwang
    Eun Jung Lee
    Chulhong Kim
    Yosep Chong
    Scientific Reports, 11
  • [43] Prognostic Gene Expression Profiling in Lung Adenocarcinoma Using Deep Learning Applied to Whole-Slide Images
    Murchan, P.
    Baird, A. -M.
    Broin, P. O.
    Sheils, O.
    Finn, S.
    JOURNAL OF THORACIC ONCOLOGY, 2024, 19 (10) : S164 - S164
  • [44] Deep learning to assess microsatellite instability directly from histopathological whole slide images in endometrial cancer
    Wang, Ching-Wei
    Muzakky, Hikam
    Firdi, Nabila Puspita
    Liu, Tzu-Chien
    Lai, Po-Jen
    Wang, Yu-Chi
    Yu, Mu-Hsien
    Chao, Tai-Kuang
    NPJ DIGITAL MEDICINE, 2024, 7 (01):
  • [45] A deep learning approach to assess the predominant tumor growth pattern in whole-slide images of lung adenocarcinoma
    Swiderska-Chadaj, Zaneta
    Nurzynska, Karolina
    Grala, Bartlomiej
    Grunberg, Katrien
    van Der Woude, Lieke
    Looijen-Salamon, Monika
    Walts, Ann E.
    Markiewicz, Tomasz
    Ciompi, Francesco
    Gertych, Arkadiusz
    MEDICAL IMAGING 2020: DIGITAL PATHOLOGY, 2021, 11320
  • [46] Deep learning-based histopathological segmentation for whole slide images of colorectal cancer in a compressed domain
    Kim, Hyeongsub
    Yoon, Hongjoon
    Thakur, Nishant
    Hwang, Gyoyeon
    Lee, Eun Jung
    Kim, Chulhong
    Chong, Yosep
    SCIENTIFIC REPORTS, 2021, 11 (01)
  • [47] Deep learning for automatic diagnosis of gastric dysplasia using whole-slide histopathology images in endoscopic specimens
    Shi, Zhongyue
    Zhu, Chuang
    Zhang, Yu
    Wang, Yakun
    Hou, Weihua
    Li, Xue
    Lu, Jun
    Guo, Xinmeng
    Xu, Feng
    Jiang, Xingran
    Wang, Ying
    Liu, Jun
    Jin, Mulan
    GASTRIC CANCER, 2022, 25 (04) : 751 - 760
  • [48] An Artificial Intelligent System for Prostate Cancer Diagnosis in Whole Slide Images
    Saha, Sajib
    Vignarajan, Janardhan
    Flesch, Adam
    Jelinko, Patrik
    Gorog, Petra
    Szep, Eniko
    Toth, Csaba
    Gombas, Peter
    Schvarcz, Tibor
    Mihaly, Orsolya
    Kapin, Marianna
    Zub, Alexandra
    Kuthi, Levente
    Tiszlavicz, Laszlo
    Glasz, Tibor
    Frost, Shaun
    JOURNAL OF MEDICAL SYSTEMS, 2024, 48 (01)
  • [49] Evaluation of a Deep Learning Model for Metastatic Squamous Cell Carcinoma Prediction From Whole Slide Images
    Abe, Makoto
    Kanavati, Fahdi
    Tsuneki, Masayuki
    ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE, 2024, 148 (12) : 1344 - 1351
  • [50] A deep learning model to predict RNA-Seq expression of tumours from whole slide images
    Schmauch, Benoit
    Romagnoni, Alberto
    Pronier, Elodie
    Saillard, Charlie
    Maille, Pascale
    Calderaro, Julien
    Kamoun, Aurelie
    Sefta, Meriem
    Toldo, Sylvain
    Zaslavskiy, Mikhail
    Clozel, Thomas
    Moarii, Matahi
    Courtiol, Pierre
    Wainrib, Gilles
    NATURE COMMUNICATIONS, 2020, 11 (01)