Published on in Vol 20, No 11 (2018): November

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/11144, first published .
An Interpretable and Expandable Deep Learning Diagnostic System for Multiple Ocular Diseases: Qualitative Study

An Interpretable and Expandable Deep Learning Diagnostic System for Multiple Ocular Diseases: Qualitative Study

An Interpretable and Expandable Deep Learning Diagnostic System for Multiple Ocular Diseases: Qualitative Study

Journals

  1. Yang J, Zhang K, Fan H, Huang Z, Xiang Y, Yang J, He L, Zhang L, Yang Y, Li R, Zhu Y, Chen C, Liu F, Yang H, Deng Y, Tan W, Deng N, Yu X, Xuan X, Xie X, Liu X, Lin H. Development and validation of deep learning algorithms for scoliosis screening using back images. Communications Biology 2019;2(1) View
  2. Zhang Y, Li F, Yuan F, Zhang K, Huo L, Dong Z, Lang Y, Zhang Y, Wang M, Gao Z, Qin Z, Shen L. Diagnosing chronic atrophic gastritis by gastroscopy using artificial intelligence. Digestive and Liver Disease 2020;52(5):566 View
  3. Zhang K, Li X, He L, Guo C, Yang Y, Dong Z, Yang H, Zhu Y, Chen C, Zhou X, Li W, Liu Z, Wu X, Liu X, Lin H. A human-in-the-loop deep learning paradigm for synergic visual evaluation in children. Neural Networks 2020;122:163 View
  4. Tobore I, Li J, Yuhang L, Al-Handarish Y, Kandwal A, Nie Z, Wang L. Deep Learning Intervention for Health Care Challenges: Some Biomedical Domain Considerations. JMIR mHealth and uHealth 2019;7(8):e11966 View
  5. Zhang K, Liu X, Jiang J, Li W, Wang S, Liu L, Zhou X, Wang L. Prediction of postoperative complications of pediatric cataract patients using data mining. Journal of Translational Medicine 2019;17(1) View
  6. Richard A, Mayag B, Talbot F, Tsoukias A, Meinard Y. What does it mean to provide decision support to a responsible and competent expert?. EURO Journal on Decision Processes 2020;8(3-4):205 View
  7. Owais M, Arsalan M, Mahmood T, Kang J, Park K. Automated Diagnosis of Various Gastrointestinal Lesions Using a Deep Learning–Based Classification and Retrieval Framework With a Large Endoscopic Database: Model Development and Validation. Journal of Medical Internet Research 2020;22(11):e18563 View
  8. Li Z, Jiang J, Chen K, Zheng Q, Liu X, Weng H, Wu S, Chen W. Development of a deep learning-based image quality control system to detect and filter out ineligible slit-lamp images: A multicenter study. Computer Methods and Programs in Biomedicine 2021;203:106048 View
  9. Li Y, Zhou D, Liu T, Shen X. Application of deep learning in image recognition and diagnosis of gastric cancer. Artificial Intelligence in Gastrointestinal Endoscopy 2021;2(2):12 View
  10. Pan Q, Zhang K, He L, Dong Z, Zhang L, Wu X, Wu Y, Gao Y. Automatically Diagnosing Disk Bulge and Disk Herniation With Lumbar Magnetic Resonance Images by Using Deep Convolutional Neural Networks: Method Development Study. JMIR Medical Informatics 2021;9(5):e14755 View
  11. Li R, Yang Y, Lin H. The critical need to establish standards for data quality in intelligent medicine. Intelligent Medicine 2021;1(2):49 View
  12. Fang X, Deshmukh M, Chee M, Soh Z, Teo Z, Thakur S, Goh J, Liu Y, Husain R, Mehta J, Wong T, Cheng C, Rim T, Tham Y. Deep learning algorithms for automatic detection of pterygium using anterior segment photographs from slit-lamp and hand-held cameras. British Journal of Ophthalmology 2022;106(12):1642 View
  13. Wang N, Zhang Y, Wang W, Ye Z, Chen H, Hu G, Ouyang D. How can machine learning and multiscale modeling benefit ocular drug development?. Advanced Drug Delivery Reviews 2023;196:114772 View
  14. Ji Q, Jiang Y, Qu L, Yang Q, Zhang H. An Image Diagnosis Algorithm for Keratitis Based on Deep Learning. Neural Processing Letters 2022;54(3):2007 View
  15. Hui S, Dong L, Zhang K, Nie Z, Jiang X, Li H, Hou Z, Ding J, Wang Y, Li D. Noninvasive identification of Benign and malignant eyelid tumors using clinical images via deep learning system. Journal of Big Data 2022;9(1) View
  16. Amorim J, Abreu P, Fernandez A, Reyes M, Santos J, Abreu M. Interpreting Deep Machine Learning Models: An Easy Guide for Oncologists. IEEE Reviews in Biomedical Engineering 2023;16:192 View
  17. Zhang H, Liu Y, Zhang K, Hui S, Feng Y, Luo J, Li Y, Wei W. Validation of the Relationship Between Iris Color and Uveal Melanoma Using Artificial Intelligence With Multiple Paths in a Large Chinese Population. Frontiers in Cell and Developmental Biology 2021;9 View
  18. Zhang Z, Wang Y, Zhang H, Samusak A, Rao H, Xiao C, Abula M, Cao Q, Dai Q. Artificial intelligence-assisted diagnosis of ocular surface diseases. Frontiers in Cell and Developmental Biology 2023;11 View
  19. Xu W, Jin L, Zhu P, He K, Yang W, Wu M. Implementation and Application of an Intelligent Pterygium Diagnosis System Based on Deep Learning. Frontiers in Psychology 2021;12 View
  20. Zhou W, Dong L, Zhang K, Wang Q, Shao L, Yang Q, Liu Y, Fang L, Shi X, Zhang C, Zhang R, Li H, Wu H, Wei W. Deep Learning for Automatic Detection of Recurrent Retinal Detachment after Surgery Using Ultra‐Widefield Fundus Images: A Single‐Center Study. Advanced Intelligent Systems 2022;4(9) View
  21. Zhang X, Hu Y, Xiao Z, Fang J, Higashita R, Liu J. Machine Learning for Cataract Classification/Grading on Ophthalmic Imaging Modalities: A Survey. Machine Intelligence Research 2022;19(3):184 View
  22. Liao J, Liu L, Duan H, Huang Y, Zhou L, Chen L, Wang C. Using a Convolutional Neural Network and Convolutional Long Short-term Memory to Automatically Detect Aneurysms on 2D Digital Subtraction Angiography Images: Framework Development and Validation. JMIR Medical Informatics 2022;10(3):e28880 View
  23. Li J, Wang S, Hu S, Sun Y, Wang Y, Xu P, Ye J. Class-Aware Attention Network for infectious keratitis diagnosis using corneal photographs. Computers in Biology and Medicine 2022;151:106301 View
  24. Luo J, Chen Y, Yang Y, Zhang K, Liu Y, Zhao H, Dong L, Xu J, Li Y, Wei W. Prognosis Prediction of Uveal Melanoma After Plaque Brachytherapy Based on Ultrasound With Machine Learning. Frontiers in Medicine 2022;8 View
  25. Won Y, Lee H, Kim Y, Han G, Chung T, Ro Y, Lim D. Deep learning-based classification system of bacterial keratitis and fungal keratitis using anterior segment images. Frontiers in Medicine 2023;10 View
  26. Zhang R, Dong L, Li R, Zhang K, Li Y, Zhao H, Shi J, Ge X, Xu X, Jiang L, Shi X, Zhang C, Zhou W, Xu L, Wu H, Li H, Yu C, Li J, Ma J, Wei W. Automatic retinoblastoma screening and surveillance using deep learning. British Journal of Cancer 2023;129(3):466 View
  27. Zhang Y, Zhang K, Ding Y, Liu S, Wang M, Wang X, Qin Z, Zhang X, Ma T, Hu F, Li P, Feng L. Deep transfer learning from ordinary to capsule esophagogastroduodenoscopy for image quality controlling. Engineering Reports 2024;6(5) View
  28. Ahn H, Lee M, Seong S, Lee M, Na G, Chun I, Kim Y, Hong C. BioEdge: Accelerating Object Detection in Bioimages with Edge-Based Distributed Inference. Electronics 2023;12(21):4544 View
  29. Brasse J, Broder H, Förster M, Klier M, Sigler I. Explainable artificial intelligence in information systems: A review of the status quo and future research directions. Electronic Markets 2023;33(1) View
  30. Zhang K, Zhang Y, Ding Y, Wang M, Bai P, Wang X, Qin Z, Zhang X, Ma T, Hu F, Feng L, Wei W, Li P. Anatomical sites identification in both ordinary and capsule gastroduodenoscopy via deep learning. Biomedical Signal Processing and Control 2024;90:105911 View
  31. Wan C, Mao Y, Xi W, Zhang Z, Wang J, Yang W. DBPF-net: dual-branch structural feature extraction reinforcement network for ocular surface disease image classification. Frontiers in Medicine 2024;10 View
  32. Du K, Dong L, Zhang K, Guan M, Chen C, Xie L, Kong W, Li H, Zhang R, Zhou W, Wu H, Dong H, Wei W. Deep learning system for screening AIDS-related cytomegalovirus retinitis with ultra-wide-field fundus images. Heliyon 2024;10(10):e30881 View

Books/Policy Documents

  1. Nova S, Rahman M, Hosen A. Rhythms in Healthcare. View
  2. Escobar-Linero E, Muñoz-Saavedra L, Luna-Perejón F, Civit-Masot J, Rivas-Pérez M, Domínguez-Morales M, Balcells A. Recent Advancements in Smart Remote Patient Monitoring, Wearable Devices, and Diagnostics Systems. View
  3. Das P, Nayak R. Intelligent Control, Robotics, and Industrial Automation. View