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### [Machine Learning](#content) ### [Machine Learning](#content)
#### 有监督学习 #### 有监督学习
+ **Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network** 1. **Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network** Nature Medicine 25, 6569(2019)
[paper](./Application Related/Machine Learning/Supervised learning/2019-Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network.pdf)
**Awni Y. Hannun Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H. Tison, Codie Bourn, Mintu P. Turakhia and Andrew Y. Ng *Awni Y. Hannun Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H. Tison, Codie Bourn, Mintu P. Turakhia and Andrew Y. Ng*
#### 无监督学习
1. **Machine learning-based phenogrouping in heart failure to identify responders to cardiac resynchronization therapy** European Journal of Heart Failure (2018)
*Maja Cikes1, Sergio Sanchez-Martinez, Brian Claggett, Nicolas Duchateau, Gemma Piella, Constantine Butakoff, Anne Catherine Pouleur, Dorit Knappe, Tor Biering-Sørensen, Valentina Kutyifa, Arthur Moss, Kenneth Stein, Scott D. Solomon, and Bart Bijnens*
### [Deep Learning](#content) ### [Deep Learning](#content)
### [Radiomics](#content) ### [Radiomics](#content)
#### 非超声影像
1. **Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer** Clinical Cancer Research (2017)
*Zhenyu Liu, Xiao-Yan Zhang,Yan-Jie Shi, Lin Wang, Hai-Tao Zhu, Zhenchao Tang, Shuo Wang, Xiao-Ting Li, Jie Tian, and Ying-Shi Sun*
#### 超声影像
1. **面向淋巴结病变多分类鉴别的弹性和 B 型 双模态超声影像组学** 生物医学工程学杂志 2019年12月第36卷第6期
*石颉1, 2江建伟3常婉英3陈曼3张麒1, 2*
### [Combination](#content) ### [Combination](#content)
#### 硕士学位论文
1. **基于深度学习的医学CT图像中器官的区域检测** 南京师范大学 (2018)
*嵇伟伟*
1. **基于影像组学和深度迁移学习的超声图像肝纤维化评估方法研究** 深圳大学 (2019)
*赵万明*
## [Related Research Platform](#content) ## [Related Research Platform](#content)
+ [中国科学院分子影像重点实验室](http://www.radiomics.net.cn/blog/3) + [中国科学院分子影像重点实验室](http://www.radiomics.net.cn/blog/3)