BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

1853 related articles for article (PubMed ID: 31957737)

  • 41. Performance of deep neural network-based artificial intelligence method in diabetic retinopathy screening: a systematic review and meta-analysis of diagnostic test accuracy.
    Wang S; Zhang Y; Lei S; Zhu H; Li J; Wang Q; Yang J; Chen S; Pan H
    Eur J Endocrinol; 2020 Jun; 183(1):41-49. PubMed ID: 32504495
    [TBL] [Abstract][Full Text] [Related]  

  • 42. Artificial intelligence-enabled screening for diabetic retinopathy: a real-world, multicenter and prospective study.
    Zhang Y; Shi J; Peng Y; Zhao Z; Zheng Q; Wang Z; Liu K; Jiao S; Qiu K; Zhou Z; Yan L; Zhao D; Jiang H; Dai Y; Su B; Gu P; Su H; Wan Q; Peng Y; Liu J; Hu L; Ke T; Chen L; Xu F; Dong Q; Terzopoulos D; Ning G; Xu X; Ding X; Wang W
    BMJ Open Diabetes Res Care; 2020 Oct; 8(1):. PubMed ID: 33087340
    [TBL] [Abstract][Full Text] [Related]  

  • 43. Diabetic Retinopathy Screening Using Artificial Intelligence and Handheld Smartphone-Based Retinal Camera.
    Malerbi FK; Andrade RE; Morales PH; Stuchi JA; Lencione D; de Paulo JV; Carvalho MP; Nunes FS; Rocha RM; Ferraz DA; Belfort R
    J Diabetes Sci Technol; 2022 May; 16(3):716-723. PubMed ID: 33435711
    [TBL] [Abstract][Full Text] [Related]  

  • 44. Artificial intelligence in diabetic retinopathy screening: clinical assessment using handheld fundus camera in a real-life setting.
    Lupidi M; Danieli L; Fruttini D; Nicolai M; Lassandro N; Chhablani J; Mariotti C
    Acta Diabetol; 2023 Aug; 60(8):1083-1088. PubMed ID: 37154944
    [TBL] [Abstract][Full Text] [Related]  

  • 45. Development of an artificial intelligence system to classify pathology and clinical features on retinal fundus images.
    Stevenson CH; Hong SC; Ogbuehi KC
    Clin Exp Ophthalmol; 2019 May; 47(4):484-489. PubMed ID: 30370587
    [TBL] [Abstract][Full Text] [Related]  

  • 46. 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]  

  • 47. Validation of Smartphone Based Retinal Photography for Diabetic Retinopathy Screening.
    Rajalakshmi R; Arulmalar S; Usha M; Prathiba V; Kareemuddin KS; Anjana RM; Mohan V
    PLoS One; 2015; 10(9):e0138285. PubMed ID: 26401839
    [TBL] [Abstract][Full Text] [Related]  

  • 48. Clinical validation of a smartphone-based retinal camera for diabetic retinopathy screening.
    de Oliveira JAE; Nakayama LF; Zago Ribeiro L; de Oliveira TVF; Choi SNJH; Neto EM; Cardoso VS; Dib SA; Melo GB; Regatieri CVS; Malerbi FK
    Acta Diabetol; 2023 Aug; 60(8):1075-1081. PubMed ID: 37149834
    [TBL] [Abstract][Full Text] [Related]  

  • 49. Feasibility and accuracy of the screening for diabetic retinopathy using a fundus camera and an artificial intelligence pre-evaluation application.
    Piatti A; Romeo F; Manti R; Doglio M; Tartaglino B; Nada E; Giorda CB
    Acta Diabetol; 2024 Jan; 61(1):63-68. PubMed ID: 37676288
    [TBL] [Abstract][Full Text] [Related]  

  • 50. Tele-Ophthalmology Versus Face-to-Face Retinal Consultation for Assessment of Diabetic Retinopathy in Diabetes Care Centers in India: A Multicenter Cross-Sectional Study.
    Rajalakshmi R; UmaSankari G; Prathiba V; Anjana RM; Unnikrishnan R; Venkatesan U; JebaRani S; Shanthirani CS; Sivaprasad S; Mohan V
    Diabetes Technol Ther; 2022 Aug; 24(8):556-563. PubMed ID: 35294275
    [No Abstract]   [Full Text] [Related]  

  • 51. Validation of an autonomous artificial intelligence-based diagnostic system for holistic maculopathy screening in a routine occupational health checkup context.
    Font O; Torrents-Barrena J; Royo D; García SB; Zarranz-Ventura J; Bures A; Salinas C; Zapata MÁ
    Graefes Arch Clin Exp Ophthalmol; 2022 Oct; 260(10):3255-3265. PubMed ID: 35567610
    [TBL] [Abstract][Full Text] [Related]  

  • 52. Simple, Mobile-based Artificial Intelligence Algo
    Sosale B; Aravind SR; Murthy H; Narayana S; Sharma U; Gowda SGV; Naveenam M
    BMJ Open Diabetes Res Care; 2020 Jan; 8(1):. PubMed ID: 32049632
    [TBL] [Abstract][Full Text] [Related]  

  • 53. Artificial intelligence-based screening for diabetic retinopathy at community hospital.
    He J; Cao T; Xu F; Wang S; Tao H; Wu T; Sun L; Chen J
    Eye (Lond); 2020 Mar; 34(3):572-576. PubMed ID: 31455902
    [TBL] [Abstract][Full Text] [Related]  

  • 54. Automatic Diagnosis of Diabetic Retinopathy Stage Focusing Exclusively on Retinal Hemorrhage.
    Tokuda Y; Tabuchi H; Nagasawa T; Tanabe M; Deguchi H; Yoshizumi Y; Ohara Z; Takahashi H
    Medicina (Kaunas); 2022 Nov; 58(11):. PubMed ID: 36422220
    [No Abstract]   [Full Text] [Related]  

  • 55. Validation of Automated Screening for Referable Diabetic Retinopathy With an Autonomous Diagnostic Artificial Intelligence System in a Spanish Population.
    Shah A; Clarida W; Amelon R; Hernaez-Ortega MC; Navea A; Morales-Olivas J; Dolz-Marco R; Verbraak F; Jorda PP; van der Heijden AA; Peris Martinez C
    J Diabetes Sci Technol; 2021 May; 15(3):655-663. PubMed ID: 32174153
    [TBL] [Abstract][Full Text] [Related]  

  • 56. 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]  

  • 57. Simple methods for the lesion detection and severity grading of diabetic retinopathy by image processing and transfer learning.
    Sugeno A; Ishikawa Y; Ohshima T; Muramatsu R
    Comput Biol Med; 2021 Oct; 137():104795. PubMed ID: 34488028
    [TBL] [Abstract][Full Text] [Related]  

  • 58. Artificial Intelligence for the Detection of Diabetic Retinopathy in Primary Care: Protocol for Algorithm Development.
    Vidal-Alaball J; Royo Fibla D; Zapata MA; Marin-Gomez FX; Solans Fernandez O
    JMIR Res Protoc; 2019 Feb; 8(2):e12539. PubMed ID: 30707105
    [TBL] [Abstract][Full Text] [Related]  

  • 59. Accuracy of Detection and Grading of Diabetic Retinopathy and Diabetic Macular Edema Using Teleretinal Screening.
    Date RC; Shen KL; Shah BM; Sigalos-Rivera MA; Chu YI; Weng CY
    Ophthalmol Retina; 2019 Apr; 3(4):343-349. PubMed ID: 31014687
    [TBL] [Abstract][Full Text] [Related]  

  • 60. Validation of a Deep Learning Algorithm for Diabetic Retinopathy.
    Romero-Aroca P; Verges-Puig R; de la Torre J; Valls A; Relaño-Barambio N; Puig D; Baget-Bernaldiz M
    Telemed J E Health; 2020 Aug; 26(8):1001-1009. PubMed ID: 31682189
    [No Abstract]   [Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 93.