Warning: Undefined array key "mm" in /www/wwwroot/www.ai-bt.com/si.php on line 10 Deprecated: trim(): Passing null to parameter #1 ($string) of type string is deprecated in /www/wwwroot/www.ai-bt.com/si.php on line 10 Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

Literature DB >> 30032794

Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

Donald C Hood¹, Carlos Gustavo De Moraes².

Abstract

Entities: Disease

Mesh：

Year: 2018 PMID： 30032794 DOI： 10.1016/j.ophtha.2018.04.020

Source DB: PubMed Journal: Ophthalmology ISSN： 0161-6420 Impact factor: 12.079

Keyword Cloud
Cited

× No keyword cloud information.

10 in total

1. Artificial Intelligence Screening for Diabetic Retinopathy: the Real-World Emerging Application.

Authors: Valentina Bellemo; Gilbert Lim; Tyler Hyungtaek Rim; Gavin S W Tan; Carol Y Cheung; SriniVas Sadda; Ming-Guang He; Adnan Tufail; Mong Li Lee; Wynne Hsu; Daniel Shu Wei Ting
Journal: Curr Diab Rep Date: 2019-07-31 Impact factor: 4.810

2. Glaucoma diagnosis using multi-feature analysis and a deep learning technique.

Authors: Nahida Akter; John Fletcher; Stuart Perry; Matthew P Simunovic; Nancy Briggs; Maitreyee Roy
Journal: Sci Rep Date: 2022-05-16 Impact factor: 4.996

3. Health care cost and benefits of artificial intelligence-assisted population-based glaucoma screening for the elderly in remote areas of China: a cost-offset analysis.

Authors: Xuan Xiao; Long Xue; Lin Ye; Hongzheng Li; Yunzhen He
Journal: BMC Public Health Date: 2021-06-04 Impact factor: 3.295

4. Computer-aided detection and abnormality score for the outer retinal layer in optical coherence tomography.

Authors: Tyler Hyungtaek Rim; Aaron Yuntai Lee; Daniel S Ting; Kelvin Yi Chong Teo; Hee Seung Yang; Hyeonmin Kim; Geunyoung Lee; Zhen Ling Teo; Alvin Teo Wei Jun; Kengo Takahashi; Tea Keun Yoo; Sung Eun Kim; Yasuo Yanagi; Ching-Yu Cheng; Sung Soo Kim; Tien Yin Wong; Chui Ming Gemmy Cheung
Journal: Br J Ophthalmol Date: 2021-04-19 Impact factor: 5.908

5. Deep Learning-Based Automated Classification of Multi-Categorical Abnormalities From Optical Coherence Tomography Images.

Authors: Wei Lu; Yan Tong; Yue Yu; Yiqiao Xing; Changzheng Chen; Yin Shen
Journal: Transl Vis Sci Technol Date: 2018-12-28 Impact factor: 3.283

6. Evaluation of Automatic Monitoring of Instillation Adherence Using Eye Dropper Bottle Sensor and Deep Learning in Patients With Glaucoma.

Authors: Kazuaki Nishimura; Hitoshi Tabuchi; Shunsuke Nakakura; Yoshiki Nakatani; Akira Yorihiro; Shouichi Hasegawa; Hirotaka Tanabe; Asuka Noguchi; Ryota Aoki; Yoshiaki Kiuchi
Journal: Transl Vis Sci Technol Date: 2019-06-27 Impact factor: 3.283

Efficacy of a Deep Learning System for Detecting Glaucomatous Optic Neuropathy Based on Color Fundus Photographs.

1. Artificial Intelligence Screening for Diabetic Retinopathy: the Real-World Emerging Application.

2. Glaucoma diagnosis using multi-feature analysis and a deep learning technique.

3. Health care cost and benefits of artificial intelligence-assisted population-based glaucoma screening for the elderly in remote areas of China: a cost-offset analysis.

4. Computer-aided detection and abnormality score for the outer retinal layer in optical coherence tomography.

5. Deep Learning-Based Automated Classification of Multi-Categorical Abnormalities From Optical Coherence Tomography Images.

6. Evaluation of Automatic Monitoring of Instillation Adherence Using Eye Dropper Bottle Sensor and Deep Learning in Patients With Glaucoma.

7. Machine learning-based prediction model using clinico-pathologic factors for papillary thyroid carcinoma recurrence.

8. Prediction of the Fundus Tessellation Severity With Machine Learning Methods.

Review 9. Applications of Artificial Intelligence in Myopia: Current and Future Directions.

10. Glaucoma Screening: Is AI the Answer?