###### tags: `陳`

# 文獻探討_Cataract 過去成果

- IEEE
- .autorpa.lib.ncnu.edu.tw

- 表格

| Author | Year | abstract | Accuracy | Method | DataBase | Link |
| --- | --- | --- | --- | --- | --- | --- |
| Sigit et al.[ ] | 2019 | Text | 85% | Single layer perceptron | Jemursari Hospital (Surabaya,Indonesia) | [link](https://ieeexplore-ieee-org.autorpa.lib.ncnu.edu.tw/document/8982445 )|
| Qian et al.[ ] | 2018 | Text | 96.1% | CNN-SqueezeNet | No.2 Hospital (Changshu,Jiangsu,China) | [link](https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8642133) |
| Pathak et al.[ ] | 2016 | Text | 98% | K-means | M.K. Singh, Professor, Dept. of Ophthalmology, Institute of Medical Sciences BHU(India) | [link](https://www.mdpi.com/2079-9292/5/3/57/htm) |
| Jagadish Nayak[ ] | 2013 | Text | 88% | SVM | Head of Ophthalmology department, Kasturba Medical College (Manipal, India) | [link](http://www.iaeng.org/publication/WCECS2013/WCECS2013_pp542-545.pdf) |
| Fuadah et al.[ ] | 2015 | Text | 94.5% | KNN | Cicendo Eye Hospital (Bandung,Indonesia)|[link](https://ieeexplore.ieee.org/abstract/document/7219958?casa_token=zulODrUwjUAAAAA:JJKxQ1ls2tYUHoGa9eNxGOMhWvHOmnErgS8UVQz8FJEsjU7jgX3m2R9qLBpdCU01urXfgF)|
| Yang et al.[ ] | 2013 | Text | Train: 82.1% Test: 82.9% | BP | Yang Hua from TONGREN Hospital(Beijing,China) | [link](https://ieeexplore-ieee-org.autorpa.lib.ncnu.edu.tw/document/6720761)|
| Li et al.[ ] | 2009 | Text | Nuclear: Cortical: | SVM | Singapore A*STAR SBIC |[link](https://ieeexplore-ieee-org.autorpa.lib.ncnu.edu.tw/document/5304895)*|
| Zheng et al.[ ] | 2014 | Text | Two-class: 95.22% Four-class: 81.52% | LDA with AdaBoost| N/A | [link](https://ieeexplore-ieee-org.autorpa.lib.ncnu.edu.tw/abstract/document/6958452?casa_token=Q04aJlYbRbkAAAAA:WM5z6cmLijhMtEq29hfE5lBC2bIGQhu4kMbC-cmWjCKYdv6E29urjx8mu-hUW9pwcDr_ZmBO4Q) |
| Xu et al.[ ] | 2013 | Text | 69% | Regression model | N/A | [link](https://link.springer.com/chapter/10.1007/978-3-642-40763-5_58#citeas) |
| Xu et al.[ ] | ~~2019~~ 2021 | Text | 85.7% 76.6% (two time)| Transfer Induced Attention Network (TIA-Net) | N/A |~~[link](https://www.researchgate.net/publication/332860885_A_Hybrid_Global-Local_Representation_CNN_Model_for_Automatic_Cataract_Grading)~~<br/>[link](https://biomedical-engineering-online.biomedcentral.com/articles/10.1186/s12938-021-00877-5)|
| Yang et al.[ ] | 2016 | Text | detection: 93.2% grading: 84.5% | Ensemble learning | Picture Archiving and Communication System (PACS) | [link](https://www.sciencedirect.com/science/article/pii/S0169260715002679)|
| The Proposed Approach | 2021 | Text | Train: 99.7% Valid: 98.7% Test: 90.8% | CNN | Train: krishnabojha[ ] Test: piygot5[ ] | N/A |

~~- The method we proposed....blabla~~

---

## 可能可用圖

- Paper: Retinal Imaging and Image Analysis
-