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Capillary.io: Publication list

  • The challenge of comprehensive nailfold videocapillaroscopy practice: a further contribution. Clin Exp Rheumatol. 2022 Oct;40(10):1926-1932.
  • External clinical validation of automated software to identify structural abnormalities and microhaemorrhages in nailfold videocapillaroscopy images. Clin Exp Rheumatol. 2023 Aug;41(8):1605-1611.
  • Capi-score: a quantitative algorithm for identifying disease patterns in nailfold videocapillaroscopy Rheumatology (Oxford). 2024 Mar 26:keae197.
  • CAPI-detect: machine learning in capillaroscopy reveals new variables influencing diagnosis. Rheumatology (Oxford). 2025 Feb 7:keaf073
  • POS0256 AUTOMATED CAPILLARY DETECTION AND IMAGE ANALYSIS SOFTWARE IN CAPILLAROSCOPY: CAPILLARY.IO Annals of the Rheumatic Diseases 2021;80:350-351.
  • POS1408 REPRODUCIBILITY OF A NEW AUTOMATIC SYSTEM (CAPILLARY.IO) IN THE ANALYSIS OF NAILFOLD CAPILLAROSCOPY IMAGES Annals of the Rheumatic Diseases 2021;80:987.
  • POS1409 AUTOMATED DETECTION OF SCLERODERMIFORM PATTERNS USING CAPILLARY.IO Annals of the Rheumatic Diseases 2021;80:987-988.
  • POS0904 UNLOCKING PRECISION IN CAPILLAROSCOPY: EXTERNAL VALIDATION OF THE CAPI-SCORE ALGORITHM FOR ACCURATE PATTERN IDENTIFICATION IN NAILFOLD VIDEOCAPILLAROSCOPY Annals of the Rheumatic Diseases 2024;83:1143-1144.
  • POS0907 THE SIGNIFICANCE OF ANALYSED MILLIMETERS IN INTERPRETING NAILFOLD CAPILLAROSCOPY IMAGES Annals of the Rheumatic Diseases 2024;83:1146-1147.

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Capillary.io is a collaborative project to offer health professionals a tool to automatically analyze capillaroscopy images, and provide a library of images that allows the professional to improve their interpretation of nailfold capillaroscopy with the help of national and international experts.