Browsing by Author "Pomerantz, Stuart"

Now showing items 1-3 of 3

    • An explainable deep-learning algorithm for the detection of acute intracranial haemorrhage from small datasets 

      Lee, Hyunkwang; Yune, Sehyo; Mansouri, Mohammad; Kim, Myeongchan; Tajmir, Shahein H.; Guerrier, Claude E.; Ebert, Sarah A.; Pomerantz, Stuart; Romero, Javier; Kamalian, Mohammad; Gonzalez, Ramon; Lev, Michael; Do, Synho (Springer Science and Business Media LLC, 2018-12-17)
      Owing to improvements in image recognition via deep learning, machine-learning algorithms could eventually be applied to automated medical diagnoses that can guide clinical decision-making. However, these algorithms remain ...

    • The Massachusetts General Hospital Acute Stroke Imaging Algorithm: An Experience and Evidence Based Approach 

      Gonzalez, Ramon Gilberto; Copen, William Alan; Schaefer, Pamela Whitney; Lev, Michael Howard; Pomerantz, Stuart R.; Rapalino, Otto; Chen, John Wen-Yueh; Hunter, George; Romero, Javier M.; Buchbinder, Bradley R.; Larvie, Mykol; Hirsch, Joshua A.; Gupta, Rajiv (BMJ Publishing Group, 2013)
      The Massachusetts General Hospital Neuroradiology Division employed an experience and evidence based approach to develop a neuroimaging algorithm to best select patients with severe ischemic strokes caused by anterior ...

    • Optimal Brain MRI Protocol for New Neurological Complaint 

      Mehan, William A.; González, R. Gilberto; Buchbinder, Bradley R.; Chen, John W.; Copen, William A.; Gupta, Rajiv; Hirsch, Joshua A.; Hunter, George J.; Hunter, Scott; Johnson, Jason M.; Kelly, Hillary R.; Larvie, Mykol; Lev, Michael H.; Pomerantz, Stuart R.; Rapalino, Otto; Rincon, Sandra; Romero, Javier M.; Schaefer, Pamela W.; Shah, Vinil (Public Library of Science, 2014)
      Background/Purpose Patients with neurologic complaints are imaged with MRI protocols that may include many pulse sequences. It has not been documented which sequences are essential. We assessed the diagnostic accuracy of ...