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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)
 
     *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)
 
     *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)  
 
     *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*