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 *

1016 related articles for article (PubMed ID: 33323271)

  • 21. Deep learning-based detection and classification of geographic atrophy using a deep convolutional neural network classifier.
    Treder M; Lauermann JL; Eter N
    Graefes Arch Clin Exp Ophthalmol; 2018 Nov; 256(11):2053-2060. PubMed ID: 30091055
    [TBL] [Abstract][Full Text] [Related]  

  • 22. SLO-Net: Enhancing Multiple Sclerosis Diagnosis Beyond Optical Coherence Tomography Using Infrared Reflectance Scanning Laser Ophthalmoscopy Images.
    Arian R; Aghababaei A; Soltanipour A; Khodabandeh Z; Rakhshani S; Iyer SB; Ashtari F; Rabbani H; Kafieh R
    Transl Vis Sci Technol; 2024 Jul; 13(7):13. PubMed ID: 39017629
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Development and Validation of a Deep Learning System to Detect Glaucomatous Optic Neuropathy Using Fundus Photographs.
    Liu H; Li L; Wormstone IM; Qiao C; Zhang C; Liu P; Li S; Wang H; Mou D; Pang R; Yang D; Zangwill LM; Moghimi S; Hou H; Bowd C; Jiang L; Chen Y; Hu M; Xu Y; Kang H; Ji X; Chang R; Tham C; Cheung C; Ting DSW; Wong TY; Wang Z; Weinreb RN; Xu M; Wang N
    JAMA Ophthalmol; 2019 Dec; 137(12):1353-1360. PubMed ID: 31513266
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Automated classification of normal and Stargardt disease optical coherence tomography images using deep learning.
    Shah M; Roomans Ledo A; Rittscher J
    Acta Ophthalmol; 2020 Sep; 98(6):e715-e721. PubMed ID: 31981283
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Deep Learning Method for Automated Classification of Anteroposterior and Posteroanterior Chest Radiographs.
    Kim TK; Yi PH; Wei J; Shin JW; Hager G; Hui FK; Sair HI; Lin CT
    J Digit Imaging; 2019 Dec; 32(6):925-930. PubMed ID: 30972585
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Automated Identification of Incomplete and Complete Retinal Epithelial Pigment and Outer Retinal Atrophy Using Machine Learning.
    Chiang JN; Corradetti G; Nittala MG; Corvi F; Rakocz N; Rudas A; Durmus B; An U; Sankararaman S; Chiu A; Halperin E; Sadda SR
    Ophthalmol Retina; 2023 Feb; 7(2):118-126. PubMed ID: 35995411
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Deep Learning Classifiers for Automated Detection of Gonioscopic Angle Closure Based on Anterior Segment OCT Images.
    Xu BY; Chiang M; Chaudhary S; Kulkarni S; Pardeshi AA; Varma R
    Am J Ophthalmol; 2019 Dec; 208():273-280. PubMed ID: 31445003
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Deep learning model for automatic image quality assessment in PET.
    Zhang H; Liu Y; Wang Y; Ma Y; Niu N; Jing H; Huo L
    BMC Med Imaging; 2023 Jun; 23(1):75. PubMed ID: 37277706
    [TBL] [Abstract][Full Text] [Related]  

  • 29. MRI-based Identification and Classification of Major Intracranial Tumor Types by Using a 3D Convolutional Neural Network: A Retrospective Multi-institutional Analysis.
    Chakrabarty S; Sotiras A; Milchenko M; LaMontagne P; Hileman M; Marcus D
    Radiol Artif Intell; 2021 Sep; 3(5):e200301. PubMed ID: 34617029
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Developing a low-cost, open-source, locally manufactured workstation and computational pipeline for automated histopathology evaluation using deep learning.
    Choudhury D; Dolezal JM; Dyer E; Kochanny S; Ramesh S; Howard FM; Margalus JR; Schroeder A; Schulte J; Garassino MC; Kather JN; Pearson AT
    EBioMedicine; 2024 Sep; 107():105276. PubMed ID: 39197222
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Assessment of Generative Adversarial Networks Model for Synthetic Optical Coherence Tomography Images of Retinal Disorders.
    Zheng C; Xie X; Zhou K; Chen B; Chen J; Ye H; Li W; Qiao T; Gao S; Yang J; Liu J
    Transl Vis Sci Technol; 2020 May; 9(2):29. PubMed ID: 32832202
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Evaluation of the performance of traditional machine learning algorithms, convolutional neural network and AutoML Vision in ultrasound breast lesions classification: a comparative study.
    Wan KW; Wong CH; Ip HF; Fan D; Yuen PL; Fong HY; Ying M
    Quant Imaging Med Surg; 2021 Apr; 11(4):1381-1393. PubMed ID: 33816176
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Automated Grading of Age-Related Macular Degeneration From Color Fundus Images Using Deep Convolutional Neural Networks.
    Burlina PM; Joshi N; Pekala M; Pacheco KD; Freund DE; Bressler NM
    JAMA Ophthalmol; 2017 Nov; 135(11):1170-1176. PubMed ID: 28973096
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Deep Learning Models to Predict Fatal Pneumonia Using Chest X-Ray Images.
    Anai S; Hisasue J; Takaki Y; Hara N
    Can Respir J; 2022; 2022():8026580. PubMed ID: 36465274
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs.
    Gulshan V; Peng L; Coram M; Stumpe MC; Wu D; Narayanaswamy A; Venugopalan S; Widner K; Madams T; Cuadros J; Kim R; Raman R; Nelson PC; Mega JL; Webster DR
    JAMA; 2016 Dec; 316(22):2402-2410. PubMed ID: 27898976
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Development and validation of a deep-learning algorithm for the detection of neovascular age-related macular degeneration from colour fundus photographs.
    Keel S; Li Z; Scheetz J; Robman L; Phung J; Makeyeva G; Aung K; Liu C; Yan X; Meng W; Guymer R; Chang R; He M
    Clin Exp Ophthalmol; 2019 Nov; 47(8):1009-1018. PubMed ID: 31215760
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Automated detection of erythema migrans and other confounding skin lesions via deep learning.
    Burlina PM; Joshi NJ; Ng E; Billings SD; Rebman AW; Aucott JN
    Comput Biol Med; 2019 Feb; 105():151-156. PubMed ID: 30654165
    [TBL] [Abstract][Full Text] [Related]  

  • 38. The possibility of the combination of OCT and fundus images for improving the diagnostic accuracy of deep learning for age-related macular degeneration: a preliminary experiment.
    Yoo TK; Choi JY; Seo JG; Ramasubramanian B; Selvaperumal S; Kim DW
    Med Biol Eng Comput; 2019 Mar; 57(3):677-687. PubMed ID: 30349958
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Performance of Automated Machine Learning in Predicting Outcomes of Pneumatic Retinopexy.
    Nisanova A; Yavary A; Deaner J; Ali FS; Gogte P; Kaplan R; Chen KC; Nudleman E; Grewal D; Gupta M; Wolfe J; Klufas M; Yiu G; Soltani I; Emami-Naeini P
    Ophthalmol Sci; 2024; 4(5):100470. PubMed ID: 38827487
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Learning from small data: Classifying sex from retinal images via deep learning.
    Berk A; Ozturan G; Delavari P; Maberley D; Yılmaz Ö; Oruc I
    PLoS One; 2023; 18(8):e0289211. PubMed ID: 37535591
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 51.