This grand round has already taken place.
This lecture series is designed to cover a one year cycle. The main discipline of diagnostic radiology and to afford specialists specific updates on current practice guidelines within the radiology subspecialties. Membership must be obtained to attend meetings and to receive Continuing Medical Education (CME) credits. To become a member of the Long Island Radiological Society ("LIRS"), please visit Website: http://liradsoc.org/
Dates and Times
Start: 3/12/2019 7:00 PM
End: 3/12/2019 8:00 PM
- Provide an overview of the background & basics of AI methodology, including technical and algorithmic considerations.
- Highlight important definitions and details of Convolutional Neural Networks (CNN's), including "hyper-parameters", "overfitting", "transfer learning", and "explainability".
- Discuss important pearls, pitfalls, & potential impact of medical AI in general, and imaging AI in particular.
- Describe the role of Deep Learning (DL) in radiological detection (2nd reader) and readout prioritization (triage) applications, with special attention to head CT detection & classification of intracranial hemorrhage.
- Review detailed examples of imaging AI applications, including "bone age", "CXR screening (normal vs. abnormal)", and "Head CT screening".
- Describe the potential added value versus limitations of "big data" versus "small data", as well as potential future directions.
Fox Hollow Catering
7725 Jericho Turnpike
Woodbury, NY 11797
The School of Medicine, State University of New York at Stony Brook, is accredited by the Accreditation Council for Continuing Medical Education to provide continuing medical education for physicians.
The School of Medicine, State University of New York at Stony Brook designates this live activity for a maximum of 1.00 AMA PRA Category 1 Credit(s) ™. Physicians should only claim the credit commensurate with the extent of their participation in the activity.