This event is for the Stanford community.
The use of algorithms in clinical care demands a very high level of precision for accurate detection and classification of disease. Deep learning (DL) offers a powerful toolkit necessary to handle the complex variations present in medical data, which traditional statistical or machine learning approaches have historically been unable to capture.
In this talk, I will describe the challenges and approaches for the development of high-performance DL algorithms and curation of datasets for problems in medical image diagnoses. I will also discuss the use of these algorithms as diagnostic support tools for clinicians, and challenges for the potential translation of these algorithms from the lab setting to clinical practice.