Cargando…
Artificial intelligence-based decision-making for age-related macular degeneration
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 pro...
Autores principales: | , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ivyspring International Publisher
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6332801/ https://www.ncbi.nlm.nih.gov/pubmed/30662564 http://dx.doi.org/10.7150/thno.28447 |
_version_ | 1783387432338587648 |
---|---|
author | Hwang, De-Kuang Hsu, Chih-Chien Chang, Kao-Jung Chao, Daniel Sun, Chuan-Hu Jheng, Ying-Chun Yarmishyn, Aliaksandr A. Wu, Jau-Ching Tsai, Ching-Yao Wang, Mong-Lien Peng, Chi-Hsien Chien, Ke-Hung Kao, Chung-Lan Lin, Tai-Chi Woung, Lin-Chung Chen, Shih-Jen Chiou, Shih-Hwa |
author_facet | Hwang, De-Kuang Hsu, Chih-Chien Chang, Kao-Jung Chao, Daniel Sun, Chuan-Hu Jheng, Ying-Chun Yarmishyn, Aliaksandr A. Wu, Jau-Ching Tsai, Ching-Yao Wang, Mong-Lien Peng, Chi-Hsien Chien, Ke-Hung Kao, Chung-Lan Lin, Tai-Chi Woung, Lin-Chung Chen, Shih-Jen Chiou, Shih-Hwa |
author_sort | Hwang, De-Kuang |
collection | PubMed |
description | 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 https://www.ym.edu.tw/~AI-OCT/. 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. |
format | Online Article Text |
id | pubmed-6332801 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Ivyspring International Publisher |
record_format | MEDLINE/PubMed |
spelling | pubmed-63328012019-01-18 Artificial intelligence-based decision-making for age-related macular degeneration Hwang, De-Kuang Hsu, Chih-Chien Chang, Kao-Jung Chao, Daniel Sun, Chuan-Hu Jheng, Ying-Chun Yarmishyn, Aliaksandr A. Wu, Jau-Ching Tsai, Ching-Yao Wang, Mong-Lien Peng, Chi-Hsien Chien, Ke-Hung Kao, Chung-Lan Lin, Tai-Chi Woung, Lin-Chung Chen, Shih-Jen Chiou, Shih-Hwa Theranostics Research Paper 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 https://www.ym.edu.tw/~AI-OCT/. 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. Ivyspring International Publisher 2019-01-01 /pmc/articles/PMC6332801/ /pubmed/30662564 http://dx.doi.org/10.7150/thno.28447 Text en © Ivyspring International Publisher This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY-NC) license (https://creativecommons.org/licenses/by-nc/4.0/). See http://ivyspring.com/terms for full terms and conditions. |
spellingShingle | Research Paper Hwang, De-Kuang Hsu, Chih-Chien Chang, Kao-Jung Chao, Daniel Sun, Chuan-Hu Jheng, Ying-Chun Yarmishyn, Aliaksandr A. Wu, Jau-Ching Tsai, Ching-Yao Wang, Mong-Lien Peng, Chi-Hsien Chien, Ke-Hung Kao, Chung-Lan Lin, Tai-Chi Woung, Lin-Chung Chen, Shih-Jen Chiou, Shih-Hwa Artificial intelligence-based decision-making for age-related macular degeneration |
title | Artificial intelligence-based decision-making for age-related macular degeneration |
title_full | Artificial intelligence-based decision-making for age-related macular degeneration |
title_fullStr | Artificial intelligence-based decision-making for age-related macular degeneration |
title_full_unstemmed | Artificial intelligence-based decision-making for age-related macular degeneration |
title_short | Artificial intelligence-based decision-making for age-related macular degeneration |
title_sort | artificial intelligence-based decision-making for age-related macular degeneration |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6332801/ https://www.ncbi.nlm.nih.gov/pubmed/30662564 http://dx.doi.org/10.7150/thno.28447 |
work_keys_str_mv | AT hwangdekuang artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT hsuchihchien artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT changkaojung artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT chaodaniel artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT sunchuanhu artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT jhengyingchun artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT yarmishynaliaksandra artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT wujauching artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT tsaichingyao artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT wangmonglien artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT pengchihsien artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT chienkehung artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT kaochunglan artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT lintaichi artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT wounglinchung artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT chenshihjen artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration AT chioushihhwa artificialintelligencebaseddecisionmakingforagerelatedmaculardegeneration |