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 *

169 related articles for article (PubMed ID: 37552340)

  • 41. Predicting diabetic retinopathy and identifying interpretable biomedical features using machine learning algorithms.
    Tsao HY; Chan PY; Su EC
    BMC Bioinformatics; 2018 Aug; 19(Suppl 9):283. PubMed ID: 30367589
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Screening for Diabetic Retinopathy Using a Portable, Noncontact, Nonmydriatic Handheld Retinal Camera.
    Zhang W; Nicholas P; Schuman SG; Allingham MJ; Faridi A; Suthar T; Cousins SW; Prakalapakorn SG
    J Diabetes Sci Technol; 2017 Jan; 11(1):128-134. PubMed ID: 27402242
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Prevalence and risk factors for diabetic retinopathy in a cross-sectional population-based study from rural southern China: Dongguan Eye Study.
    Cui Y; Zhang M; Zhang L; Zhang L; Kuang J; Zhang G; Liu Q; Guo H; Meng Q
    BMJ Open; 2019 Sep; 9(9):e023586. PubMed ID: 31530585
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Feasibility and patient acceptability of a novel artificial intelligence-based screening model for diabetic retinopathy at endocrinology outpatient services: a pilot study.
    Keel S; Lee PY; Scheetz J; Li Z; Kotowicz MA; MacIsaac RJ; He M
    Sci Rep; 2018 Mar; 8(1):4330. PubMed ID: 29531299
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Incidence of sight-threatening diabetic retinopathy in people with Type 2 diabetes mellitus and numbers needed to screen: a systematic review.
    Groeneveld Y; Tavenier D; Blom JW; Polak BCP
    Diabet Med; 2019 Oct; 36(10):1199-1208. PubMed ID: 30677170
    [TBL] [Abstract][Full Text] [Related]  

  • 46. [Screening for diabetic retinopathy by non-mydriatic fundus photography: First national campaign in Lebanon].
    Arej N; Antoun J; Waked R; Saab C; Saleh M; Waked N
    J Fr Ophtalmol; 2019 Mar; 42(3):288-294. PubMed ID: 30857804
    [TBL] [Abstract][Full Text] [Related]  

  • 47. Screening for diabetic retinopathy in diabetic patients with a mydriasis-free, full-field flicker electroretinogram recording device.
    Zeng Y; Cao D; Yang D; Zhuang X; Yu H; Hu Y; Zhang Y; Yang C; He M; Zhang L
    Doc Ophthalmol; 2020 Jun; 140(3):211-220. PubMed ID: 31720980
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Screening for diabetic retinopathy: 1 and 3 nonmydriatic 45-degree digital fundus photographs vs 7 standard early treatment diabetic retinopathy study fields.
    Vujosevic S; Benetti E; Massignan F; Pilotto E; Varano M; Cavarzeran F; Avogaro A; Midena E
    Am J Ophthalmol; 2009 Jul; 148(1):111-8. PubMed ID: 19406376
    [TBL] [Abstract][Full Text] [Related]  

  • 49. [Using artificial intelligence as an initial triage strategy in diabetic retinopathy screening program in China].
    Li ZX; Zhang J; Fong N; He MG
    Zhonghua Yi Xue Za Zhi; 2020 Dec; 100(48):3835-3840. PubMed ID: 33371627
    [No Abstract]   [Full Text] [Related]  

  • 50. Combining transfer learning with retinal lesion features for accurate detection of diabetic retinopathy.
    Hassan D; Gill HM; Happe M; Bhatwadekar AD; Hajrasouliha AR; Janga SC
    Front Med (Lausanne); 2022; 9():1050436. PubMed ID: 36425113
    [TBL] [Abstract][Full Text] [Related]  

  • 51. Prevalence, progression, and outcomes of diabetic retinopathy during pregnancy in Indian scenario.
    Makwana T; Takkar B; Venkatesh P; Sharma JB; Gupta Y; Chawla R; Vohra R; Kriplani A; Tandon N
    Indian J Ophthalmol; 2018 Apr; 66(4):541-546. PubMed ID: 29582816
    [TBL] [Abstract][Full Text] [Related]  

  • 52. High prevalence of lower extremity peripheral artery disease in type 2 diabetes patients with proliferative diabetic retinopathy.
    Chen YW; Wang YY; Zhao D; Yu CG; Xin Z; Cao X; Shi J; Yang GR; Yuan MX; Yang JK
    PLoS One; 2015; 10(3):e0122022. PubMed ID: 25822410
    [TBL] [Abstract][Full Text] [Related]  

  • 53. [Modern approach to early diagnosis and pathogenetic treatment of diabetic retinopathy].
    Vorob'eva IV
    Vestn Oftalmol; 2016; 132(5):60-67. PubMed ID: 27911427
    [TBL] [Abstract][Full Text] [Related]  

  • 54. EyeArt artificial intelligence analysis of diabetic retinopathy in retinal screening events.
    Vought R; Vought V; Shah M; Szirth B; Bhagat N
    Int Ophthalmol; 2023 Dec; 43(12):4851-4859. PubMed ID: 37847478
    [TBL] [Abstract][Full Text] [Related]  

  • 55. Radiomics-Based Assessment of OCT Angiography Images for Diabetic Retinopathy Diagnosis.
    Carrera-Escalé L; Benali A; Rathert AC; Martín-Pinardel R; Bernal-Morales C; Alé-Chilet A; Barraso M; Marín-Martinez S; Feu-Basilio S; Rosinés-Fonoll J; Hernandez T; Vilá I; Castro-Dominguez R; Oliva C; Vinagre I; Ortega E; Gimenez M; Vellido A; Romero E; Zarranz-Ventura J
    Ophthalmol Sci; 2023 Jun; 3(2):100259. PubMed ID: 36578904
    [TBL] [Abstract][Full Text] [Related]  

  • 56. The SEE Study: Safety, Efficacy, and Equity of Implementing Autonomous Artificial Intelligence for Diagnosing Diabetic Retinopathy in Youth.
    Wolf RM; Liu TYA; Thomas C; Prichett L; Zimmer-Galler I; Smith K; Abramoff MD; Channa R
    Diabetes Care; 2021 Mar; 44(3):781-787. PubMed ID: 33479160
    [TBL] [Abstract][Full Text] [Related]  

  • 57. Diagnostic accuracy of smartphone-based artificial intelligence systems for detecting diabetic retinopathy: A systematic review and meta-analysis.
    Hasan SU; Siddiqui MAR
    Diabetes Res Clin Pract; 2023 Nov; 205():110943. PubMed ID: 37805002
    [TBL] [Abstract][Full Text] [Related]  

  • 58. THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.
    Vaghefi E; Yang S; Xie L; Hill S; Schmiedel O; Murphy R; Squirrell D
    Diabet Med; 2021 Apr; 38(4):e14386. PubMed ID: 32794618
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Evaluation of a novel artificial intelligence-based screening system for diabetic retinopathy in community of China: a real-world study.
    Ming S; Xie K; Lei X; Yang Y; Zhao Z; Li S; Jin X; Lei B
    Int Ophthalmol; 2021 Apr; 41(4):1291-1299. PubMed ID: 33389425
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Predicting the risk of diabetic retinopathy using explainable machine learning algorithms.
    Islam MM; Rahman MJ; Rabby MS; Alam MJ; Pollob SMAI; Ahmed NAMF; Tawabunnahar M; Roy DC; Shin J; Maniruzzaman M
    Diabetes Metab Syndr; 2023 Dec; 17(12):102919. PubMed ID: 38091881
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.