3. Deep Learning poses a threat and an opportunity. A concern was raised that deep learning can automate important tasks that are currently performed by radiologists. However, low hanging fruit for AI is in having some menial tasks of radiology—measuring changes of lung nodules, evaluating for changes in size of Multiple Sclerosis lesions—to be automated. Radiology has taken the lead in implementing many advanced forms of technology within healthcare. If the combined imaging workforce can embrace the adaptation of deep learning in medical imaging, then it can guide the implementation of deep learning in other subspecialties in medicine—such as using machine learning in screening colonoscopies or diagnosing electrocardiogram abnormalities for patients with cardiac disease, among others.
Related article: Q&A: AI For All Radiologists
The event was a success in providing an overview of deep learning technology. It highlighted current applications of deep learning technology in medical imaging, the strengths of these applications as well as their shortcomings. Most importantly, this event helped move the conversation of deep learning in medical imaging to a place where radiologists can shape its future. Yes, there are threats that deep learning poses to the profession of radiology. However, there are also immense opportunities for medical imaging and for all of healthcare.
Radiology will go through extensive change in the future as it becomes easier to implement deep learning algorithms in clinical care. However, the practice of radiology has embraced cutting edge advancements in healthcare and technology and through deep learning, radiologists can continue to embrace this change and shape the future of healthcare.
Max Henderson, PhD is a Senior Data Scientist that functions in a variety of roles at QxBranch, helping support projects involving quantum computation, machine learning, and data science. He has held Data Scientist positions at JPMorgan Chase & Co. and Lockheed Martin, providing technical solutions in cyber, bioinformatics, and natural language processing domains. Max has a PhD and MS from Drexel University in Physics as well as a BS in Physics from West Chester University. He can be reached through his Twitter: https://twitter.com/QxMax
Dr. Ajay Kohli is a resident physician in Radiology at Drexel University College of Medicine. He has completed an accelerated BS and MD program at Drexel University College of Medicine with clinical work at Kaiser Permanente in California. He has launched multiple entrepreneurial ventures as well as clinical studies within digital medicine which have gone on to win research competitions as well as grants (from using wearable technology in surgical oncology to using smartphones in heart failure and breast cancer management). He can be reached through his website: www.ajaykohlimd.com