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<td>&ensp;<a href="#deep-learning">2.2 Deep Learning</a></td> <td>&ensp;<a href="#deep-learning">2.2 Deep Learning</a></td>
</tr> </tr>
<tr> <tr>
<td>&emsp;<a href="#radiomics">2.3 Radiomics</a></td> <td>&emsp;<a href="#radiomics">1.3 Radiomics</a></td>
<td>&ensp;<a href="#combination">2.4 Combination</a></td> <td>&ensp;<a href="#combination">2.2 Deep Learning</a></td>
<td></td>
</tr> </tr>
<tr><td colspan="2"><a href="related-research-platform">3. Related Research Platform</a></td></tr> <tr><td colspan="2"><a href="related-research-platform">3. Related Research Platform</a></td></tr>
</table> </table>
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## [Application related](#content) ## [Application related](#content)
### [Machine Learning](#content) ### [Machine Learning](#content)
* #### 有监督学习
1. **Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network** Nature Medicine 25, 65–69(2019)
*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) 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* *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)
1. **Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network** Nature Medicine 25, 65–69(2019)
*Awni Y. Hannun Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H. Tison, Codie Bourn, Mintu P. Turakhia and Andrew Y. Ng*
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，硕士学位论文 (2018)
*嵇伟伟*
### [Radiomics](#content) ### [Radiomics](#content)
* #### 非超声影像 * ### 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) 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* *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 * ### 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 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* *石颉1, 2，江建伟3，常婉英3，陈曼3，张麒1, 2*
### [Combination](#content) ### [Combination](#content)
* ### Machine Learning & Radiomics
* #### 硕士学位论文 * ### Deep Learning & Radiomics
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，硕士学位论文 (2019)
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* *赵万明*