• Tajmir, Shahein H., Hyunkwang Lee, Randheer Shailam, Heather I. Gale, Jie C. Nguyen, Sjirk J. Westra, Ruth Lim, Sehyo Yune, Michael S. Gee, and Synho Do. “Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability.” Skeletal Radiology 48, no. 2 (2019): 275-283.
  • Parakh, Anushri, Hyunkwang Lee, Jeong Hyun Lee, Brian H. Eisner, Dushyant V. Sahani, and Synho Do. “Urinary Stone Detection on CT Images Using Deep Convolutional Neural Networks: Evaluation of Model Performance and Generalization.” Radiology: Artificial Intelligence 1, no. 4 (2019): e180066.
  • Yune, Sehyo, Hyunkwang Lee, Myeongchan Kim, Shahein H. Tajmir, Michael S. Gee, and Synho Do. “Beyond Human Perception: Sexual Dimorphism in Hand and Wrist Radiographs Is Discernible by a Deep Learning Model.” Journal of digital imaging 32, no. 4 (2019): 665-671.
  • Song, Kyoung Doo, Myeongchan Kim, and Synho Do. “The Latest Trends in the Use of Deep Learning in Radiology Illustrated Through the Stages of Deep Learning Algorithm Development.” Journal of the Korean Society of Radiology 80, no. 2 (2019): 202-212.
  • Muelly, Michael C., and Lily Peng. “Spotting brain bleeding after sparse training.” Nature Biomedical Engineering 3, no. 3 (2019): 161. (Worth to read, Commentary for our “Explainable AI”  paper from Google Cloud Team.)

LMIC WebMaster • August 29, 2015

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