These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

147 related articles for article (PubMed ID: 36508904)

  • 1. A one-dimensional convolutional neural network based deep learning for high accuracy classification of transformation stages in esophageal squamous cell carcinoma tissue using micro-FTIR.
    Yang H; Li X; Zhang S; Li Y; Zhu Z; Shen J; Dai N; Zhou F
    Spectrochim Acta A Mol Biomol Spectrosc; 2023 Mar; 289():122210. PubMed ID: 36508904
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.
    Tokai Y; Yoshio T; Aoyama K; Horie Y; Yoshimizu S; Horiuchi Y; Ishiyama A; Tsuchida T; Hirasawa T; Sakakibara Y; Yamada T; Yamaguchi S; Fujisaki J; Tada T
    Esophagus; 2020 Jul; 17(3):250-256. PubMed ID: 31980977
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Raman spectroscopy and machine learning for the classification of esophageal squamous carcinoma.
    Huang W; Shang Q; Xiao X; Zhang H; Gu Y; Yang L; Shi G; Yang Y; Hu Y; Yuan Y; Ji A; Chen L
    Spectrochim Acta A Mol Biomol Spectrosc; 2022 Nov; 281():121654. PubMed ID: 35878494
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Diagnostic outcomes of esophageal cancer by artificial intelligence using convolutional neural networks.
    Horie Y; Yoshio T; Aoyama K; Yoshimizu S; Horiuchi Y; Ishiyama A; Hirasawa T; Tsuchida T; Ozawa T; Ishihara S; Kumagai Y; Fujishiro M; Maetani I; Fujisaki J; Tada T
    Gastrointest Endosc; 2019 Jan; 89(1):25-32. PubMed ID: 30120958
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep learning prediction of esophageal squamous cell carcinoma invasion depth from arterial phase enhanced CT images: a binary classification approach.
    Wu X; Wu H; Miao S; Cao G; Su H; Pan J; Xu Y
    BMC Med Inform Decis Mak; 2024 Jan; 24(1):3. PubMed ID: 38167058
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Study on breast cancerization and isolated diagnosis in situ by HOF-ATR-MIR spectroscopy with deep learning.
    Shang H; Wu Q; Wu J; Zhou S; Wang Z; Wang H; Yin J
    Spectrochim Acta A Mol Biomol Spectrosc; 2024 Oct; 319():124546. PubMed ID: 38824755
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Survival risk prediction model for ESCC based on relief feature selection and CNN.
    Wang Y; Zhu C; Wang Y; Sun J; Ling D; Wang L
    Comput Biol Med; 2022 Jun; 145():105460. PubMed ID: 35364307
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Deep-learning-based classification of desmoplastic reaction on H&E predicts poor prognosis in oesophageal squamous cell carcinoma.
    Kouzu K; Nearchou IP; Kajiwara Y; Tsujimoto H; Lillard K; Kishi Y; Ueno H
    Histopathology; 2022 Aug; 81(2):255-263. PubMed ID: 35758184
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Use of a convolutional neural network for classifying microvessels of superficial esophageal squamous cell carcinomas.
    Uema R; Hayashi Y; Tashiro T; Saiki H; Kato M; Amano T; Tani M; Yoshihara T; Inoue T; Kimura K; Iwatani S; Sakatani A; Yoshii S; Tsujii Y; Shinzaki S; Iijima H; Takehara T
    J Gastroenterol Hepatol; 2021 Aug; 36(8):2239-2246. PubMed ID: 33694189
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Rapid and sensitive detection of esophageal cancer by FTIR spectroscopy of serum and plasma.
    Chen H; Li X; Zhang S; Yang H; Gao Q; Zhou F
    Photodiagnosis Photodyn Ther; 2022 Dec; 40():103177. PubMed ID: 36602070
    [TBL] [Abstract][Full Text] [Related]  

  • 11. AI-assisted identification of intrapapillary capillary loops in magnification endoscopy for diagnosing early-stage esophageal squamous cell carcinoma: a preliminary study.
    Wang J; Long Q; Liang Y; Song J; Feng Y; Li P; Sun W; Zhao L
    Med Biol Eng Comput; 2023 Jul; 61(7):1631-1648. PubMed ID: 36841920
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A Novel Deep Learning System for Diagnosing Early Esophageal Squamous Cell Carcinoma: A Multicenter Diagnostic Study.
    Tang D; Wang L; Jiang J; Liu Y; Ni M; Fu Y; Guo H; Wang Z; An F; Zhang K; Hu Y; Zhan Q; Xu G; Zou X
    Clin Transl Gastroenterol; 2021 Aug; 12(8):e00393. PubMed ID: 34346911
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Classification for invasion depth of esophageal squamous cell carcinoma using a deep neural network compared with experienced endoscopists.
    Nakagawa K; Ishihara R; Aoyama K; Ohmori M; Nakahira H; Matsuura N; Shichijo S; Nishida T; Yamada T; Yamaguchi S; Ogiyama H; Egawa S; Kishida O; Tada T
    Gastrointest Endosc; 2019 Sep; 90(3):407-414. PubMed ID: 31077698
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Targeted bisulfite sequencing identified a panel of DNA methylation-based biomarkers for esophageal squamous cell carcinoma (ESCC).
    Pu W; Wang C; Chen S; Zhao D; Zhou Y; Ma Y; Wang Y; Li C; Huang Z; Jin L; Guo S; Wang J; Wang M
    Clin Epigenetics; 2017; 9():129. PubMed ID: 29270239
    [TBL] [Abstract][Full Text] [Related]  

  • 15. The Discovery and Validation of Biomarkers for the Diagnosis of Esophageal Squamous Dysplasia and Squamous Cell Carcinoma.
    Couch G; Redman JE; Wernisch L; Newton R; Malhotra S; Dawsey SM; Lao-Sirieix P; Fitzgerald RC
    Cancer Prev Res (Phila); 2016 Jul; 9(7):558-66. PubMed ID: 27072986
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Effectiveness of deep learning classifiers in histopathological diagnosis of oral squamous cell carcinoma by pathologists.
    Sukegawa S; Ono S; Tanaka F; Inoue Y; Hara T; Yoshii K; Nakano K; Takabatake K; Kawai H; Katsumitsu S; Nakai F; Nakai Y; Miyazaki R; Murakami S; Nagatsuka H; Miyake M
    Sci Rep; 2023 Jul; 13(1):11676. PubMed ID: 37468501
    [TBL] [Abstract][Full Text] [Related]  

  • 17. ORAOV1 overexpression in esophageal squamous cell carcinoma and esophageal dysplasia: a possible biomarker of progression and poor prognosis in esophageal carcinoma.
    Li M; Cui X; Shen Y; Dong H; Liang W; Chen Y; Hu J; Li S; Kong J; Li H; Zhao J; Li F
    Hum Pathol; 2015 May; 46(5):707-15. PubMed ID: 25732110
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Effectiveness of screening endoscopy for esophageal squamous cell carcinoma in Japanese males.
    Nezu Y; Manabe N; Yoda Y; Haruma K
    United European Gastroenterol J; 2022 Oct; 10(8):868-873. PubMed ID: 35976761
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Feasibility of using P16 methylation as a cytologic marker for esophageal squamous cell carcinoma screening: A pilot study.
    Fan Z; Qin Y; Zhou J; Chen R; Gu J; Li M; Zhou J; Li X; Lin D; Wang J; Deng D; Wei W
    Cancer Med; 2022 Nov; 11(21):4033-4042. PubMed ID: 35352503
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Automated classification of cells into multiple classes in epithelial tissue of oral squamous cell carcinoma using transfer learning and convolutional neural network.
    Das N; Hussain E; Mahanta LB
    Neural Netw; 2020 Aug; 128():47-60. PubMed ID: 32416467
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.