AI is a paradigm shifting force particularly for medical imaging. Radiology is one of the most data rich specialties. Information in images that is imperceptible to the eye are a particularly rich source of data for research outcomes.
New teams are needed. Many of the key people/stakeholders are not part of a traditional radiology team. They include in addition to radiologists, computer scientists, pathologists, oncologists, biologists, biostatisticians and post docs and students. Many of these people are only found at a university – particularly a tech campus.
**For institutions without a connected university/technology, how can robust AI teams be built to create and support a Data Science Institute?**
There are many other challenges using the data to build models and moving toward a more automated algorithmic approach.
Challenges include ethical issues such as patient confidentiality and legal issues. Who owns the data? How do you develop and maintain trust with patients and referrers? How does academics and industry work together?