Kuniyoshi Kanai
University of California, Berkeley
5 Papers
24 Citations
Kuniyoshi Kanai is an academic researcher from University of California, Berkeley. The author has contributed to research in topics: Fundus (eye) & Fundus photography. The author has an hindex of 3, co-authored 4 publications.
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Papers
Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning.
Avinash V. Varadarajan,Pinal Bavishi,Paisan Ruamviboonsuk,Peranut Chotcomwongse,Subhashini Venugopalan,Arunachalam Narayanaswamy,Jorge Cuadros,Kuniyoshi Kanai,George H. Bresnick,Mongkol Tadarati,Sukhum Silpa-archa,Jirawut Limwattanayingyong,Variya Nganthavee,Joseph R. Ledsam,Pearse A. Keane,Greg S. Corrado,Lily Peng,Dale R. Webster +17 more
TL;DR: A deep learning model is presented that can predict the presence of diabetic macular edema from color fundus photographs with superior specificity and positive predictive value compared to retinal specialists.
Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning
Avinash V. Varadarajan,Pinal Bavishi,Paisan Raumviboonsuk,Peranut Chotcomwongse,Subhashini Venugopalan,Arunachalam Narayanaswamy,Jorge Cuadros,Kuniyoshi Kanai,George H. Bresnick,Mongkol Tadarati,Sukhum Silpa-archa,Jirawut Limwattanayingyong,Variya Nganthavee,Joseph R. Ledsam,Pearse A. Keane,Greg S. Corrado,Lily Peng,Dale R. Webster +17 more
TL;DR: In this article, a deep learning model was used to predict center-involved diabetic macular edema (ci-DME) using color fundus photographs and achieved an ROC-AUC of 0.89 (95% CI: 0.87-0.91).
Case Series: Unbiased Deep Sequencing Analysis of Acute Infectious Conjunctivitis in an Ambulatory Eye Center in Berkeley, California
Kuniyoshi Kanai,Meredith Whiteside,Michael Wong,Tammy La,Maryam Nassiri,Sam Bum Lee,Sze Kei Yeung,Adrienne Coulter,Kevin Ruder,Cindi Chen,David Liu,Thomas Abraham,Armin Hinterwirth,Thomas M. Lietman,Thuy Doan,Gerami D. Seitzman +15 more
TL;DR: In this paper , the authors used unbiased deep sequencing to identify causative pathogens of infectious conjunctivitis, potentially allowing for improved approaches to diagnosis and management, and they identified associated pathogens, including human adenovirus D, Haemophilus influenzae, Chlamydia trachomatis, and human coronavirus 229E.
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A Revised Approach for the Detection of Sight-Threatening Diabetic Macular Edema.
TL;DR: A sectors approach shows good screening test characteristics for the detection of CSME in monoscopic images using a sectors approach and may be easily incorporated in the automated diabetic retinopathy detection algorithms.