BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

451 related articles for article (PubMed ID: 32307321)

  • 1. Application of deep learning image assessment software VeriSee™ for diabetic retinopathy screening.
    Hsieh YT; Chuang LM; Jiang YD; Chang TJ; Yang CM; Yang CH; Chan LW; Kao TY; Chen TC; Lin HC; Tsai CH; Chen M
    J Formos Med Assoc; 2021 Jan; 120(1 Pt 1):165-171. PubMed ID: 32307321
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Application of artificial intelligence-based dual-modality analysis combining fundus photography and optical coherence tomography in diabetic retinopathy screening in a community hospital.
    Liu R; Li Q; Xu F; Wang S; He J; Cao Y; Shi F; Chen X; Chen J
    Biomed Eng Online; 2022 Jul; 21(1):47. PubMed ID: 35859144
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Artificial intelligence using deep learning to screen for referable and vision-threatening diabetic retinopathy in Africa: a clinical validation study.
    Bellemo V; Lim ZW; Lim G; Nguyen QD; Xie Y; Yip MYT; Hamzah H; Ho J; Lee XQ; Hsu W; Lee ML; Musonda L; Chandran M; Chipalo-Mutati G; Muma M; Tan GSW; Sivaprasad S; Menon G; Wong TY; Ting DSW
    Lancet Digit Health; 2019 May; 1(1):e35-e44. PubMed ID: 33323239
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Validation of Artificial Intelligence Algorithm in the Detection and Staging of Diabetic Retinopathy through Fundus Photography: An Automated Tool for Detection and Grading of Diabetic Retinopathy.
    Pawar B; Lobo SN; Joseph M; Jegannathan S; Jayraj H
    Middle East Afr J Ophthalmol; 2021; 28(2):81-86. PubMed ID: 34759664
    [TBL] [Abstract][Full Text] [Related]  

  • 6. An Automated Grading System for Detection of Vision-Threatening Referable Diabetic Retinopathy on the Basis of Color Fundus Photographs.
    Li Z; Keel S; Liu C; He Y; Meng W; Scheetz J; Lee PY; Shaw J; Ting D; Wong TY; Taylor H; Chang R; He M
    Diabetes Care; 2018 Dec; 41(12):2509-2516. PubMed ID: 30275284
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automated diabetic retinopathy detection in smartphone-based fundus photography using artificial intelligence.
    Rajalakshmi R; Subashini R; Anjana RM; Mohan V
    Eye (Lond); 2018 Jun; 32(6):1138-1144. PubMed ID: 29520050
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Automatic Grading System for Diabetic Retinopathy Diagnosis Using Deep Learning Artificial Intelligence Software.
    Wang XN; Dai L; Li ST; Kong HY; Sheng B; Wu Q
    Curr Eye Res; 2020 Dec; 45(12):1550-1555. PubMed ID: 32410471
    [No Abstract]   [Full Text] [Related]  

  • 9. Validation of Deep Convolutional Neural Network-based algorithm for detection of diabetic retinopathy - Artificial intelligence versus clinician for screening.
    Shah P; Mishra DK; Shanmugam MP; Doshi B; Jayaraj H; Ramanjulu R
    Indian J Ophthalmol; 2020 Feb; 68(2):398-405. PubMed ID: 31957737
    [TBL] [Abstract][Full Text] [Related]  

  • 10. The diagnostic accuracy of single- and five-field fundus photography in diabetic retinopathy screening by primary care physicians.
    Srihatrai P; Hlowchitsieng T
    Indian J Ophthalmol; 2018 Jan; 66(1):94-97. PubMed ID: 29283131
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Assessment of diabetic retinopathy using two ultra-wide-field fundus imaging systems, the Clarus® and Optos™ systems.
    Hirano T; Imai A; Kasamatsu H; Kakihara S; Toriyama Y; Murata T
    BMC Ophthalmol; 2018 Dec; 18(1):332. PubMed ID: 30572870
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Application of an Anomaly Detection Model to Screen for Ocular Diseases Using Color Retinal Fundus Images: Design and Evaluation Study.
    Han Y; Li W; Liu M; Wu Z; Zhang F; Liu X; Tao L; Li X; Guo X
    J Med Internet Res; 2021 Jul; 23(7):e27822. PubMed ID: 34255681
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Cross-Camera External Validation for Artificial Intelligence Software in Diagnosis of Diabetic Retinopathy.
    Tsai MJ; Hsieh YT; Tsai CH; Chen M; Hsieh AT; Tsai CW; Chen ML
    J Diabetes Res; 2022; 2022():5779276. PubMed ID: 35308093
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Simultaneous Diagnosis of Severity and Features of Diabetic Retinopathy in Fundus Photography Using Deep Learning.
    Wang J; Bai Y; Xia B
    IEEE J Biomed Health Inform; 2020 Dec; 24(12):3397-3407. PubMed ID: 32750975
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Medios- An offline, smartphone-based artificial intelligence algorithm for the diagnosis of diabetic retinopathy.
    Sosale B; Sosale AR; Murthy H; Sengupta S; Naveenam M
    Indian J Ophthalmol; 2020 Feb; 68(2):391-395. PubMed ID: 31957735
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A convolutional neural network for the screening and staging of diabetic retinopathy.
    Shaban M; Ogur Z; Mahmoud A; Switala A; Shalaby A; Abu Khalifeh H; Ghazal M; Fraiwan L; Giridharan G; Sandhu H; El-Baz AS
    PLoS One; 2020; 15(6):e0233514. PubMed ID: 32569310
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Nonmydriatic ultrawide field retinal imaging compared with dilated standard 7-field 35-mm photography and retinal specialist examination for evaluation of diabetic retinopathy.
    Silva PS; Cavallerano JD; Sun JK; Noble J; Aiello LM; Aiello LP
    Am J Ophthalmol; 2012 Sep; 154(3):549-559.e2. PubMed ID: 22626617
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automated Identification of Diabetic Retinopathy Using Deep Learning.
    Gargeya R; Leng T
    Ophthalmology; 2017 Jul; 124(7):962-969. PubMed ID: 28359545
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy.
    Sayres R; Taly A; Rahimy E; Blumer K; Coz D; Hammel N; Krause J; Narayanaswamy A; Rastegar Z; Wu D; Xu S; Barb S; Joseph A; Shumski M; Smith J; Sood AB; Corrado GS; Peng L; Webster DR
    Ophthalmology; 2019 Apr; 126(4):552-564. PubMed ID: 30553900
    [TBL] [Abstract][Full Text] [Related]  

  • 20. In-Person Verification of Deep Learning Algorithm for Diabetic Retinopathy Screening Using Different Techniques Across Fundus Image Devices.
    Wongchaisuwat N; Trinavarat A; Rodanant N; Thoongsuwan S; Phasukkijwatana N; Prakhunhungsit S; Preechasuk L; Wongchaisuwat P
    Transl Vis Sci Technol; 2021 Nov; 10(13):17. PubMed ID: 34767624
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 23.