Get our free extension to see links to code for papers anywhere online!

Chrome logo  Add to Chrome

Firefox logo Add to Firefox
Picture for Atilla P. Kiraly

Atilla P. Kiraly
Alert button

Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases


Oct 22, 2020
Zaid Nabulsi, Andrew Sellergren, Shahar Jamshy, Charles Lau, Eddie Santos, Atilla P. Kiraly, Wenxing Ye, Jie Yang, Sahar Kazemzadeh, Jin Yu, Raju Kalidindi, Mozziyar Etemadi, Florencia Garcia Vicente, David Melnick, Greg S. Corrado, Lily Peng, Krish Eswaran, Daniel Tse, Neeral Beladia, Yun Liu, Po-Hsuan Cameron Chen, Shravya Shetty

Add code
Alert button

Figure 1 for Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases
Figure 2 for Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases
Figure 3 for Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases
Figure 4 for Deep Learning for Distinguishing Normal versus Abnormal Chest Radiographs and Generalization to Unseen Diseases

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email

Deep Adversarial Context-Aware Landmark Detection for Ultrasound Imaging


May 28, 2018
Ahmet Tuysuzoglu, Jeremy Tan, Kareem Eissa, Atilla P. Kiraly, Mamadou Diallo, Ali Kamen

Add code
Alert button

Figure 1 for Deep Adversarial Context-Aware Landmark Detection for Ultrasound Imaging
Figure 2 for Deep Adversarial Context-Aware Landmark Detection for Ultrasound Imaging
Figure 3 for Deep Adversarial Context-Aware Landmark Detection for Ultrasound Imaging
Figure 4 for Deep Adversarial Context-Aware Landmark Detection for Ultrasound Imaging

   Access Paper or Ask Questions
  • Share via Twitter
  • Share via Facebook
  • Share via LinkedIn
  • Share via Whatsapp
  • Share via Messenger
  • Share via Email