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 *

119 related articles for article (PubMed ID: 38918566)

  • 61. WINROP algorithm for prediction of sight threatening retinopathy of prematurity: Initial experience in Indian preterm infants.
    Sanghi G; Narang A; Narula S; Dogra MR
    Indian J Ophthalmol; 2018 Jan; 66(1):110-113. PubMed ID: 29283134
    [TBL] [Abstract][Full Text] [Related]  

  • 62. Validation of WINROP algorithm as screening tool of retinopathy of prematurity among Egyptian preterm neonates.
    Fares A; Abdelmonaim S; Sayed D; Sadek S; Abdulrazek A; Helmy Y; Maher S
    Eye (Lond); 2024 Jun; 38(8):1562-1566. PubMed ID: 38310200
    [TBL] [Abstract][Full Text] [Related]  

  • 63. The photographic screening for retinopathy of prematurity study (photo-ROP). Primary outcomes.
    Photographic Screening for Retinopathy of Prematurity (Photo-ROP) Cooperative Group
    Retina; 2008 Mar; 28(3 Suppl):S47-54. PubMed ID: 18317345
    [TBL] [Abstract][Full Text] [Related]  

  • 64. 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]  

  • 65. Assessment of a Tele-education System to Enhance Retinopathy of Prematurity Training by International Ophthalmologists-in-Training in Mexico.
    Patel SN; Martinez-Castellanos MA; Berrones-Medina D; Swan R; Ryan MC; Jonas KE; Ostmo S; Campbell JP; Chiang MF; Chan RVP; ;
    Ophthalmology; 2017 Jul; 124(7):953-961. PubMed ID: 28385303
    [TBL] [Abstract][Full Text] [Related]  

  • 66. ADS-Net: attention-awareness and deep supervision based network for automatic detection of retinopathy of prematurity.
    Peng Y; Chen Z; Zhu W; Shi F; Wang M; Zhou Y; Xiang D; Chen X; Chen F
    Biomed Opt Express; 2022 Aug; 13(8):4087-4101. PubMed ID: 36032570
    [TBL] [Abstract][Full Text] [Related]  

  • 67. 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]  

  • 68. Validation of DIGIROP models and decision support tool for prediction of treatment for retinopathy of prematurity on a contemporary Swedish cohort.
    Pivodic A; E H Smith L; Hård AL; Löfqvist C; Almeida AC; Al-Hawasi A; Larsson E; Lundgren P; Sunnqvist B; Tornqvist K; Wallin A; Holmstrom G; Gränse L
    Br J Ophthalmol; 2023 Aug; 107(8):1132-1138. PubMed ID: 35277395
    [TBL] [Abstract][Full Text] [Related]  

  • 69. Association of Biomarker-Based Artificial Intelligence With Risk of Racial Bias in Retinal Images.
    Coyner AS; Singh P; Brown JM; Ostmo S; Chan RVP; Chiang MF; Kalpathy-Cramer J; Campbell JP;
    JAMA Ophthalmol; 2023 Jun; 141(6):543-552. PubMed ID: 37140902
    [TBL] [Abstract][Full Text] [Related]  

  • 70. Influence of Fluorescein Angiography on the Diagnosis and Management of Retinopathy of Prematurity.
    Klufas MA; Patel SN; Ryan MC; Patel Gupta M; Jonas KE; Ostmo S; Martinez-Castellanos MA; Berrocal AM; Chiang MF; Chan RV
    Ophthalmology; 2015 Aug; 122(8):1601-8. PubMed ID: 26028345
    [TBL] [Abstract][Full Text] [Related]  

  • 71. Development of a deep learning-based image eligibility verification system for detecting and filtering out ineligible fundus images: A multicentre study.
    Li Z; Jiang J; Zhou H; Zheng Q; Liu X; Chen K; Weng H; Chen W
    Int J Med Inform; 2021 Mar; 147():104363. PubMed ID: 33388480
    [TBL] [Abstract][Full Text] [Related]  

  • 72. Accurate prediction of glaucoma from colour fundus images with a convolutional neural network that relies on active and transfer learning.
    Hemelings R; Elen B; Barbosa-Breda J; Lemmens S; Meire M; Pourjavan S; Vandewalle E; Van de Veire S; Blaschko MB; De Boever P; Stalmans I
    Acta Ophthalmol; 2020 Feb; 98(1):e94-e100. PubMed ID: 31344328
    [TBL] [Abstract][Full Text] [Related]  

  • 73. Oxygenation Fluctuations Associated with Severe Retinopathy of Prematurity: Insights from a Multimodal Deep Learning Approach.
    Lin WC; Jordan BK; Scottoline B; Ostmo SR; Coyner AS; Singh P; Kalpathy-Cramer J; Erdogmus D; Chan RVP; Chiang MF; Campbell JP
    Ophthalmol Sci; 2024; 4(2):100417. PubMed ID: 38059124
    [TBL] [Abstract][Full Text] [Related]  

  • 74. Development and international validation of custom-engineered and code-free deep-learning models for detection of plus disease in retinopathy of prematurity: a retrospective study.
    Wagner SK; Liefers B; Radia M; Zhang G; Struyven R; Faes L; Than J; Balal S; Hennings C; Kilduff C; Pooprasert P; Glinton S; Arunakirinathan M; Giannakis P; Braimah IZ; Ahmed ISH; Al-Feky M; Khalid H; Ferraz D; Vieira J; Jorge R; Husain S; Ravelo J; Hinds AM; Henderson R; Patel HI; Ostmo S; Campbell JP; Pontikos N; Patel PJ; Keane PA; Adams G; Balaskas K
    Lancet Digit Health; 2023 Jun; 5(6):e340-e349. PubMed ID: 37088692
    [TBL] [Abstract][Full Text] [Related]  

  • 75. Accuracy of retinopathy of prematurity image-based diagnosis by pediatric ophthalmology fellows: implications for training.
    Myung JS; Paul Chan RV; Espiritu MJ; Williams SL; Granet DB; Lee TC; Weissgold DJ; Chiang MF
    J AAPOS; 2011 Dec; 15(6):573-8. PubMed ID: 22153403
    [TBL] [Abstract][Full Text] [Related]  

  • 76. Assessing the Efficacy of Synthetic Optic Disc Images for Detecting Glaucomatous Optic Neuropathy Using Deep Learning.
    Chaurasia AK; MacGregor S; Craig JE; Mackey DA; Hewitt AW
    Transl Vis Sci Technol; 2024 Jun; 13(6):1. PubMed ID: 38829624
    [TBL] [Abstract][Full Text] [Related]  

  • 77. The Use of Postnatal Weight Gain Algorithms to Predict Severe or Type 1 Retinopathy of Prematurity: A Systematic Review and Meta-analysis.
    Athikarisamy S; Desai S; Patole S; Rao S; Simmer K; Lam GC
    JAMA Netw Open; 2021 Nov; 4(11):e2135879. PubMed ID: 34812847
    [TBL] [Abstract][Full Text] [Related]  

  • 78. Using ROPScore and CHOP ROP for early prediction of retinopathy of prematurity in a Chinese population.
    Sun H; Dong Y; Liu Y; Chen Q; Wang Y; Cheng B; Qin S; Meng L; Li S; Zhang Y; Zhang A; Yan W; Dong Y; Cheng S; Li M; Yu Z
    Ital J Pediatr; 2021 Feb; 47(1):39. PubMed ID: 33602298
    [TBL] [Abstract][Full Text] [Related]  

  • 79. Evaluation of a Deep Learning-Derived Quantitative Retinopathy of Prematurity Severity Scale.
    Campbell JP; Kim SJ; Brown JM; Ostmo S; Chan RVP; Kalpathy-Cramer J; Chiang MF;
    Ophthalmology; 2021 Jul; 128(7):1070-1076. PubMed ID: 33121959
    [TBL] [Abstract][Full Text] [Related]  

  • 80. Detection of Optic Disc Abnormalities in Color Fundus Photographs Using Deep Learning.
    Liu TYA; Wei J; Zhu H; Subramanian PS; Myung D; Yi PH; Hui FK; Unberath M; Ting DSW; Miller NR
    J Neuroophthalmol; 2021 Sep; 41(3):368-374. PubMed ID: 34415271
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 6.