Performance of a Deep Learning Diabetic Retinopathy Algorithm in India.

Journal: JAMA network open
PMID: 40105843

Abstract

IMPORTANCE: While prospective studies have investigated the accuracy of artificial intelligence (AI) for detection of diabetic retinopathy (DR) and diabetic macular edema (DME), to date, little published data exist on the clinical performance of these algorithms.

Authors

  • Arthur Brant
    Byers Eye Institute, Stanford University School of Medicine, Stanford, CA, USA.
  • Preeti Singh
    Division of Surgical Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA.
  • Xiang Yin
    College of Environmental Science and Engineering, Biomedical Multidisciplinary Innovation Research Institute, Shanghai East Hospital, Tongji University, Shanghai 200092, People's Republic of China.
  • Lu Yang
    Division of Mood Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Jay Nayar
    Google Health, Palo Alto, CA, USA.
  • Divleen Jeji
    Google Health, Palo Alto, CA, USA.
  • Yossi Matias
    Google Research, Google LLC, 1600 Amphitheatre Parkway, Mountain View, CA, USA.
  • Greg S Corrado
    Google Health, Palo Alto, CA USA.
  • Dale R Webster
    Google Inc, Mountain View, California.
  • Sunny Virmani
    Verily Life Sciences LLC, South San Francisco, California, USA.
  • Anchintha Meenu
    Aravind Eye Hospital, Madurai, India.
  • Naresh Babu Kannan
    Aravind Eye Hospital, Madurai, India.
  • Jonathan Krause
    Artificial Intelligence Laboratory, Computer Science Department, Stanford University, Stanford, CA 94305.
  • Florence Thng
    Verily Life Sciences, Mountain View, CA.
  • Lily Peng
    Google Inc, Mountain View, California.
  • Yun Liu
    Google Health, Palo Alto, CA USA.
  • Kasumi Widner
    Google Inc, Mountain View, California.
  • Kim Ramasamy
    Aravind Eye Hospital, Madurai, India.

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