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 *

308 related articles for article (PubMed ID: 34402800)

  • 1. Gender Prediction for a Multiethnic Population via Deep Learning Across Different Retinal Fundus Photograph Fields: Retrospective Cross-sectional Study.
    Betzler BK; Yang HHS; Thakur S; Yu M; Quek TC; Soh ZD; Lee G; Tham YC; Wong TY; Rim TH; Cheng CY
    JMIR Med Inform; 2021 Aug; 9(8):e25165. PubMed ID: 34402800
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep Learning Models for the Screening of Cognitive Impairment Using Multimodal Fundus Images.
    Shi XH; Ju L; Dong L; Zhang RH; Shao L; Yan YN; Wang YX; Fu XF; Chen YZ; Ge ZY; Wei WB
    Ophthalmol Retina; 2024 Jul; 8(7):666-677. PubMed ID: 38280426
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Development and Validation of Deep Learning Models for Screening Multiple Abnormal Findings in Retinal Fundus Images.
    Son J; Shin JY; Kim HD; Jung KH; Park KH; Park SJ
    Ophthalmology; 2020 Jan; 127(1):85-94. PubMed ID: 31281057
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep Learning and Transfer Learning for Optic Disc Laterality Detection: Implications for Machine Learning in Neuro-Ophthalmology.
    Liu TYA; Ting DSW; Yi PH; Wei J; Zhu H; Subramanian PS; Li T; Hui FK; Hager GD; Miller NR
    J Neuroophthalmol; 2020 Jun; 40(2):178-184. PubMed ID: 31453913
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Computer-aided recognition of myopic tilted optic disc using deep learning algorithms in fundus photography.
    Cho BH; Lee DY; Park KA; Oh SY; Moon JH; Lee GI; Noh H; Chung JK; Kang MC; Chung MJ
    BMC Ophthalmol; 2020 Oct; 20(1):407. PubMed ID: 33036582
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Deep Learning for Automated Sorting of Retinal Photographs.
    Rim TH; Soh ZD; Tham YC; Yang HHS; Lee G; Kim Y; Nusinovici S; Ting DSW; Wong TY; Cheng CY
    Ophthalmol Retina; 2020 Aug; 4(8):793-800. PubMed ID: 32362553
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Detecting glaucoma from multi-modal data using probabilistic deep learning.
    Huang X; Sun J; Gupta K; Montesano G; Crabb DP; Garway-Heath DF; Brusini P; Lanzetta P; Oddone F; Turpin A; McKendrick AM; Johnson CA; Yousefi S
    Front Med (Lausanne); 2022; 9():923096. PubMed ID: 36250081
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Prediction of systemic biomarkers from retinal photographs: development and validation of deep-learning algorithms.
    Rim TH; Lee G; Kim Y; Tham YC; Lee CJ; Baik SJ; Kim YA; Yu M; Deshmukh M; Lee BK; Park S; Kim HC; Sabayanagam C; Ting DSW; Wang YX; Jonas JB; Kim SS; Wong TY; Cheng CY
    Lancet Digit Health; 2020 Oct; 2(10):e526-e536. PubMed ID: 33328047
    [TBL] [Abstract][Full Text] [Related]  

  • 9. From Machine to Machine: An OCT-Trained Deep Learning Algorithm for Objective Quantification of Glaucomatous Damage in Fundus Photographs.
    Medeiros FA; Jammal AA; Thompson AC
    Ophthalmology; 2019 Apr; 126(4):513-521. PubMed ID: 30578810
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A deep learning algorithm to detect chronic kidney disease from retinal photographs in community-based populations.
    Sabanayagam C; Xu D; Ting DSW; Nusinovici S; Banu R; Hamzah H; Lim C; Tham YC; Cheung CY; Tai ES; Wang YX; Jonas JB; Cheng CY; Lee ML; Hsu W; Wong TY
    Lancet Digit Health; 2020 Jun; 2(6):e295-e302. PubMed ID: 33328123
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. Detection of Progressive Glaucomatous Optic Nerve Damage on Fundus Photographs with Deep Learning.
    Medeiros FA; Jammal AA; Mariottoni EB
    Ophthalmology; 2021 Mar; 128(3):383-392. PubMed ID: 32735906
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.
    Li Z; He Y; Keel S; Meng W; Chang RT; He M
    Ophthalmology; 2018 Aug; 125(8):1199-1206. PubMed ID: 29506863
    [TBL] [Abstract][Full Text] [Related]  

  • 14. [A deep-learning model for the assessment of coronary heart disease and related risk factors via the evaluation of retinal fundus photographs].
    Ding YD; Zhang Y; He LQ; Fu M; Zhao X; Huang LK; Wang B; Chen YZ; Wang ZH; Ma ZQ; Zeng Y
    Zhonghua Xin Xue Guan Bing Za Zhi; 2022 Dec; 50(12):1201-1206. PubMed ID: 36517441
    [No Abstract]   [Full Text] [Related]  

  • 15. Deep Learning Detection of Early Retinal Peripheral Degeneration From Ultra-Widefield Fundus Photographs of Asymptomatic Young Adult (17-19 Years) Candidates to Airforce Cadets.
    Wu T; Ju L; Fu X; Wang B; Ge Z; Liu Y
    Transl Vis Sci Technol; 2024 Feb; 13(2):1. PubMed ID: 38300623
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Effects of Hypertension, Diabetes, and Smoking on Age and Sex Prediction from Retinal Fundus Images.
    Kim YD; Noh KJ; Byun SJ; Lee S; Kim T; Sunwoo L; Lee KJ; Kang SH; Park KH; Park SJ
    Sci Rep; 2020 Mar; 10(1):4623. PubMed ID: 32165702
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Application of a deep learning system in glaucoma screening and further classification with colour fundus photographs: a case control study.
    Hung KH; Kao YC; Tang YH; Chen YT; Wang CH; Wang YC; Lee OK
    BMC Ophthalmol; 2022 Dec; 22(1):483. PubMed ID: 36510171
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Deep learning-based automated detection of glaucomatous optic neuropathy on color fundus photographs.
    Li F; Yan L; Wang Y; Shi J; Chen H; Zhang X; Jiang M; Wu Z; Zhou K
    Graefes Arch Clin Exp Ophthalmol; 2020 Apr; 258(4):851-867. PubMed ID: 31989285
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Artificial Intelligence to Detect Papilledema from Ocular Fundus Photographs.
    Milea D; Najjar RP; Zhubo J; Ting D; Vasseneix C; Xu X; Aghsaei Fard M; Fonseca P; Vanikieti K; Lagrèze WA; La Morgia C; Cheung CY; Hamann S; Chiquet C; Sanda N; Yang H; Mejico LJ; Rougier M-B; Kho R; Thi Ha Chau T; Singhal S; Gohier P; Clermont-Vignal C; Cheng C-Y; Jonas JB; Yu-Wai-Man P; Fraser CL; Chen JJ; Ambika S; Miller NR; Liu Y; Newman NJ; Wong TY; Biousse V;
    N Engl J Med; 2020 Apr; 382(18):1687-1695. PubMed ID: 32286748
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning.
    Poplin R; Varadarajan AV; Blumer K; Liu Y; McConnell MV; Corrado GS; Peng L; Webster DR
    Nat Biomed Eng; 2018 Mar; 2(3):158-164. PubMed ID: 31015713
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.