Artificial intelligence-based decision-making for age-related macular degeneration

De Kuang Hwang, Chih Chien Hsu, Kao Jung Chang, Daniel Chao, Chuan Hu Sun, Ying Chun Jheng, Aliaksandr A. Yarmishyn, Jau Ching Wu, Ching Yao Tsai, Mong Lien Wang, Chi Hsien Peng, Ke Hung Chien, Chung Lan Kao, Tai Chi Lin, Lin Chung Woung, Shih Jen Chen, Shih Hwa Chiou*


研究成果: Article同行評審

110 引文 斯高帕斯(Scopus)


Artificial intelligence (AI) based on convolutional neural networks (CNNs) has a great potential to enhance medical workflow and improve health care quality. Of particular interest is practical implementation of such AI-based software as a cloud-based tool aimed for telemedicine, the practice of providing medical care from a distance using electronic interfaces. Methods: In this study, we used a dataset of labeled 35,900 optical coherence tomography (OCT) images obtained from age-related macular degeneration (AMD) patients and used them to train three types of CNNs to perform AMD diagnosis. Results: Here, we present an AI- and cloud-based telemedicine interaction tool for diagnosis and proposed treatment of AMD. Through deep learning process based on the analysis of preprocessed optical coherence tomography (OCT) imaging data, our AI-based system achieved the same image discrimination rate as that of retinal specialists in our hospital. The AI platform’s detection accuracy was generally higher than 90% and was significantly superior (p < 0.001) to that of medical students (69.4% and 68.9%) and equal (p = 0.99) to that of retinal specialists (92.73% and 91.90%). Furthermore, it provided appropriate treatment recommendations comparable to those of retinal specialists. Conclusions: We therefore developed a website for realistic cloud computing based on this AI platform, available at Patients can upload their OCT images to the website to verify whether they have AMD and require treatment. Using an AI-based cloud service represents a real solution for medical imaging diagnostics and telemedicine.

頁(從 - 到)232-245
出版狀態Published - 2019


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