BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

444 related articles for article (PubMed ID: 33828217)

  • 21. Deep learning algorithms for detection of diabetic macular edema in OCT images: A systematic review and meta-analysis.
    Li HY; Wang DX; Dong L; Wei WB
    Eur J Ophthalmol; 2023 Jan; 33(1):278-290. PubMed ID: 35473414
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Unassisted Clinicians Versus Deep Learning-Assisted Clinicians in Image-Based Cancer Diagnostics: Systematic Review With Meta-analysis.
    Xue P; Si M; Qin D; Wei B; Seery S; Ye Z; Chen M; Wang S; Song C; Zhang B; Ding M; Zhang W; Bai A; Yan H; Dang L; Zhao Y; Rezhake R; Zhang S; Qiao Y; Qu Y; Jiang Y
    J Med Internet Res; 2023 Mar; 25():e43832. PubMed ID: 36862499
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Diagnostic Accuracy of Artificial Intelligence Based on Imaging Data for Preoperative Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Systematic Review and Meta-Analysis.
    Zhang J; Huang S; Xu Y; Wu J
    Front Oncol; 2022; 12():763842. PubMed ID: 35280776
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Accuracy of fundus autofluorescence imaging for the diagnosis and monitoring of retinal conditions: a systematic review.
    Frampton GK; Kalita N; Payne L; Colquitt J; Loveman E
    Health Technol Assess; 2016 Apr; 20(31):1-108. PubMed ID: 27115052
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Artificial intelligence and deep learning in ophthalmology.
    Ting DSW; Pasquale LR; Peng L; Campbell JP; Lee AY; Raman R; Tan GSW; Schmetterer L; Keane PA; Wong TY
    Br J Ophthalmol; 2019 Feb; 103(2):167-175. PubMed ID: 30361278
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Deep learning in ophthalmology: The technical and clinical considerations.
    Ting DSW; Peng L; Varadarajan AV; Keane PA; Burlina PM; Chiang MF; Schmetterer L; Pasquale LR; Bressler NM; Webster DR; Abramoff M; Wong TY
    Prog Retin Eye Res; 2019 Sep; 72():100759. PubMed ID: 31048019
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Multimodal imaging interpreted by graders to detect re-activation of diabetic eye disease in previously treated patients: the EMERALD diagnostic accuracy study.
    Lois N; Cook J; Wang A; Aldington S; Mistry H; Maredza M; McAuley D; Aslam T; Bailey C; Chong V; Ghanchi F; Scanlon P; Sivaprasad S; Steel D; Styles C; Azuara-Blanco A; Prior L; Waugh N
    Health Technol Assess; 2021 May; 25(32):1-104. PubMed ID: 34060440
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Digital breast tomosynthesis for breast cancer detection: a diagnostic test accuracy systematic review and meta-analysis.
    Alabousi M; Zha N; Salameh JP; Samoilov L; Sharifabadi AD; Pozdnyakov A; Sadeghirad B; Freitas V; McInnes MDF; Alabousi A
    Eur Radiol; 2020 Apr; 30(4):2058-2071. PubMed ID: 31900699
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Non-invasive testing for early detection of neovascular macular degeneration in unaffected second eyes of older adults: EDNA diagnostic accuracy study.
    Banister K; Cook JA; Scotland G; Azuara-Blanco A; Goulão B; Heimann H; Hernández R; Hogg R; Kennedy C; Sivaprasad S; Ramsay C; Chakravarthy U
    Health Technol Assess; 2022 Jan; 26(8):1-142. PubMed ID: 35119357
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Beyond the black stump: rapid reviews of health research issues affecting regional, rural and remote Australia.
    Osborne SR; Alston LV; Bolton KA; Whelan J; Reeve E; Wong Shee A; Browne J; Walker T; Versace VL; Allender S; Nichols M; Backholer K; Goodwin N; Lewis S; Dalton H; Prael G; Curtin M; Brooks R; Verdon S; Crockett J; Hodgins G; Walsh S; Lyle DM; Thompson SC; Browne LJ; Knight S; Pit SW; Jones M; Gillam MH; Leach MJ; Gonzalez-Chica DA; Muyambi K; Eshetie T; Tran K; May E; Lieschke G; Parker V; Smith A; Hayes C; Dunlop AJ; Rajappa H; White R; Oakley P; Holliday S
    Med J Aust; 2020 Dec; 213 Suppl 11():S3-S32.e1. PubMed ID: 33314144
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Deep learning for detection of age-related macular degeneration: A systematic review and meta-analysis of diagnostic test accuracy studies.
    Leng X; Shi R; Wu Y; Zhu S; Cai X; Lu X; Liu R
    PLoS One; 2023; 18(4):e0284060. PubMed ID: 37023082
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Artificial intelligence performance in detecting lymphoma from medical imaging: a systematic review and meta-analysis.
    Bai A; Si M; Xue P; Qu Y; Jiang Y
    BMC Med Inform Decis Mak; 2024 Jan; 24(1):13. PubMed ID: 38191361
    [TBL] [Abstract][Full Text] [Related]  

  • 33. The quality of reporting of diagnostic accuracy studies of optical coherence tomography in glaucoma.
    Johnson ZK; Siddiqui MA; Azuara-Blanco A
    Ophthalmology; 2007 Sep; 114(9):1607-12. PubMed ID: 17434589
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Two-field non-mydriatic fundus photography for diabetic retinopathy screening: a protocol for a systematic review and meta-analysis.
    Yu D; Dou X; Chen J; Lu Y; Ye B; Wu X; Wu Z; Li Q; Tian X; Zhou B; Deng Y; Li W; Hu X; Mou L; Pu Z
    BMJ Open; 2021 Oct; 11(10):e051761. PubMed ID: 34663665
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Insights into the growing popularity of artificial intelligence in ophthalmology.
    Dutt S; Sivaraman A; Savoy F; Rajalakshmi R
    Indian J Ophthalmol; 2020 Jul; 68(7):1339-1346. PubMed ID: 32587159
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Classifying primary central nervous system lymphoma from glioblastoma using deep learning and radiomics based machine learning approach - a systematic review and meta-analysis.
    Guha A; Goda JS; Dasgupta A; Mahajan A; Halder S; Gawde J; Talole S
    Front Oncol; 2022; 12():884173. PubMed ID: 36263203
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Search strategies to identify diagnostic accuracy studies in MEDLINE and EMBASE.
    Beynon R; Leeflang MM; McDonald S; Eisinga A; Mitchell RL; Whiting P; Glanville JM
    Cochrane Database Syst Rev; 2013 Sep; 2013(9):MR000022. PubMed ID: 24022476
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Deep learning applications in ophthalmology.
    Rahimy E
    Curr Opin Ophthalmol; 2018 May; 29(3):254-260. PubMed ID: 29528860
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Diagnostic performance of deep learning in infectious keratitis: a systematic review and meta-analysis protocol.
    Ong ZZ; Sadek Y; Liu X; Qureshi R; Liu SH; Li T; Sounderajah V; Ashrafian H; Ting DSW; Said DG; Mehta JS; Burton MJ; Dua HS; Ting DSJ
    BMJ Open; 2023 May; 13(5):e065537. PubMed ID: 37164459
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Artificial intelligence for pre-operative lymph node staging in colorectal cancer: a systematic review and meta-analysis.
    Bedrikovetski S; Dudi-Venkata NN; Kroon HM; Seow W; Vather R; Carneiro G; Moore JW; Sammour T
    BMC Cancer; 2021 Sep; 21(1):1058. PubMed ID: 34565338
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 23.