Computer Science Invited Speaker Series: Issam El Naqa, University of Michigan

Day Friday, November 22
Time 12:00 PM to 1:00 PM
Where FA-258

Issam El Naqa, professor of radiation oncology at the University of Michigan at Ann Arbor, will speak on "Towards a Practical Implementation of Artificial Intelligence in Oncology." There has been tremendous excitement in recent years in the implementation of artificial Intelligence (AI) and machine learning algorithms (ML) in routine oncology practice. This is chiefly motivated by the ability of these technologies to automate laborious routine tasks, improve efficiency, as well as enhance decision-making support of complex oncology processes from treatment planning, quality assurance, to delivery or providing more advanced prediction of outcomes and adaptation of daily treatments. However, such anticipated transformative AI/ML widespread implementation in oncology has been generally limited in scope and in some instances, it has been stagnant despite the known potentials. In this talk, we will re-visit sample AI applications in oncology, discuss the present status of AI/ML in oncology while touching on the some of the main technical and ethical challenges that are impeding broadening AI/ML current role towards delivering safer and better treatments for cancer patients. This event is funded by GSOCS, a subsidiary of GSO, using Student Activity Fee funds Refreshments will be provided!


Add to Calendar 22/11/19 12:00 PM 22/11/19 1:00 PM 15 Computer Science Invited Speaker Series: Issam El Naqa, University of Michigan Issam El Naqa, professor of radiation oncology at the University of Michigan at Ann Arbor, will speak on "Towards a Practical Implementation of Artificial Intelligence in Oncology." There has been tremendous excitement in recent years in the implementation of artificial Intelligence (AI) and machine learning algorithms (ML) in routine oncology practice. This is chiefly motivated by the ability of these technologies to automate laborious routine tasks, improve efficiency, as well as enhance decision-making support of complex oncology processes from treatment planning, quality assurance, to delivery or providing more advanced prediction of outcomes and adaptation of daily treatments. However, such anticipated transformative AI/ML widespread implementation in oncology has been generally limited in scope and in some instances, it has been stagnant despite the known potentials. In this talk, we will re-visit sample AI applications in oncology, discuss the present status of AI/ML in oncology while touching on the FA-258 DD/MM/YY