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## [Applications](#content)
### [Machine Learning](#content)
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) [[*raad*]]()
*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*
1. **Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network,** Nature Medicine 25, 65–69(2019)
1. **Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network,** Nature Medicine 25, 65–69(2019) [[*raad*]]()
*Awni Y. Hannun Pranav Rajpurkar, Masoumeh Haghpanahi, Geoffrey H. Tison, Codie Bourn, Mintu P. Turakhia and Andrew Y. Ng*
1. **Performance and Reading Time of Automated Breast US with or without Computer-aided,** Radiology 292:540–549(2019)
1. **Performance and Reading Time of Automated Breast US with or without Computer-aided,** Radiology 292:540–549(2019) [[*raad*]]()
*Shanling Yang, MD • Xican Gao, MD • Liwen Liu, PhD, MD • Rui Shu, MD • Jingru Yan, MD • Ge Zhang, MD • Yao Xiao, MD • Yan Ju, MS • Ni Zhao, MD • Hongping Song, PhD, MD*
1. **Impact of Data Presentation on Physician Performance Utilizing ArtificialIntelligence-Based Computer-Aided Diagnosis and DecisionSupport Systems,** Journal of Digital Imaging 32:408–416 (2019)
1. **Impact of Data Presentation on Physician Performance Utilizing ArtificialIntelligence-Based Computer-Aided Diagnosis and DecisionSupport Systems,** Journal of Digital Imaging 32:408–416 (2019) [[*raad*]]()
*L. Barinov1,2,3 A. Jairaj1 M. Becker3,4 SSeymour1 E. Lee3,4 A. Schram3,4&E. Lane4&A. Goldszal3,4 D. Quigley4 L. Paster3,4*
### [Deep Learning](#content)
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)
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) [*[read]*](https://github.com/vonpower/Healthcare/blob/main/Applications/Deep%20Learning/%E5%9F%BA%E4%BA%8E%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E7%9A%84%E5%8C%BB%E5%AD%A6CT%E5%9B%BE%E5%83%8F%E4%B8%AD%E5%99%A8%E5%AE%98%E7%9A%84%E5%8C%BA%E5%9F%9F%E6%A3%80%E6%B5%8B_%E5%B5%87%E4%BC%9F%E4%BC%9F.pdf)
*嵇伟伟*
1. 基于大数据和人工智能的超声医学发展现状及问题研究， 综述，肿瘤影像学，2020年第29卷第4期 [[paper]](https://github.com/vonpower/Healthcare/blob/main/Applications/Deep%20Learning/%E5%9F%BA%E4%BA%8E%E5%A4%A7%E6%95%B0%E6%8D%AE%E5%92%8C%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%E7%9A%84%E8%B6%85%E5%A3%B0%E5%8C%BB%E5%AD%A6%E5%8F%91%E5%B1%95%E7%8E%B0%E7%8A%B6%E5%8F%8A%E9%97%AE%E9%A2%98%E7%A0%94%E7%A9%B6.pdf)
1. 基于大数据和人工智能的超声医学发展现状及问题研究， 综述，肿瘤影像学，2020年第29卷第4期 [*[read]*](https://github.com/vonpower/Healthcare/blob/main/Applications/Deep%20Learning/%E5%9F%BA%E4%BA%8E%E5%A4%A7%E6%95%B0%E6%8D%AE%E5%92%8C%E4%BA%BA%E5%B7%A5%E6%99%BA%E8%83%BD%E7%9A%84%E8%B6%85%E5%A3%B0%E5%8C%BB%E5%AD%A6%E5%8F%91%E5%B1%95%E7%8E%B0%E7%8A%B6%E5%8F%8A%E9%97%AE%E9%A2%98%E7%A0%94%E7%A9%B6.pdf)
*王海星1，杨志清1，郭玲玲1，郭燕青1，张　靓1，齐　昊1，2*
1. **Management of Thyroid Nodules Seen on US Images:Deep Learning May Match Performance of Radiologists，** Radiology 292:695–701(2019) [[paper]](https://doi.org/10.1148/radiol.2019181343)
1. **Management of Thyroid Nodules Seen on US Images:Deep Learning May Match Performance of Radiologists，** Radiology 292:695–701(2019) [*[read]*](https://doi.org/10.1148/radiol.2019181343)
*Mateusz Buda, MSc • Benjamin Wildman-Tobriner, MD • Jenny K. Hoang, MBBS, MHS • David Thayer, PhD, MD •Franklin N. Tessler, MD • William D. Middleton, MD • Maciej A. Mazurowski, PhD*
### [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)
1. **Radiomics Analysis for Evaluation of Pathological Complete Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer,** Clinical Cancer Research (2017) [[*raad*]]()
*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
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 [[*raad*]]()
*石颉1, 2，江建伟3，常婉英3，陈曼3，张麒1, 2*
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* ### Deep Learning & Radiomics
1. **Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study,** GUT (2018)
1. **Deep learning Radiomics of shear wave elastography significantly improved diagnostic performance for assessing liver fibrosis in chronic hepatitis B: a prospective multicentre study,** GUT (2018) [[*raad*]]()
*Wang K, et al.*
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) [[*raad*]]()
*赵万明*