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Jan 21 2019 | AAAI | Posted In: News
Latest medical AI model and largest chest x-ray dataset ever released, thanks to a wonderful Stanford+MIT collaboration. Abstract: Jeremy Irvin, Pranav Rajpurkar, Michael Ko, Yifan Yu, Silviana Ciurea-Ilcus, Chris Chute, Henrik Marklund, Behzad Haghgoo, Robyn Ball, Katie Shpanskaya, Jayne Seekins, David A. Mong, Safwan S. Halabi, Jesse K. Sandberg, Ricky Jones, David B. Larson, Curtis P. Langlotz, Bhavik N. Patel, Matthew P. Lungren, Andrew Y. Ng
Dec 11 2018 | Radiology | Posted In: News
Remarkable work led by Greg Zaharchuk, MD, PhD, showing that diagnostic quality amyloid PET images can be generated using 1% of the PET data obtained from PET/MRI with the help of AI was recently published in Radiology.
Nov 20 2018 | Radiology | Posted In: News
Jared A. Dunnmon , Darvin Yi, Curtis P. Langlotz, Christopher Ré, Daniel L. Rubin, Matthew P. Lungren assess the ability of convolutional neural networks (CNNs) to enable high-performance automated binary classification of chest radiographs.  
September 12, 2018 -- SAN FRANCISCO - A deep-learning artificial intelligence (AI) algorithm can automatically summarize the key findings of radiology reports for x-ray images nearly as well as radiologists can, according to a Monday presentation at the Conference on Machine Intelligence in Medical Imaging (C-MIMI).  

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