Community Health Sciences - University of Manitoba
Chendong’s research focuses on mixed-effects modelling dealing with the health-related longitudinal data as well as using statistical learning methods to improve the prediction in the field of longitudinal study.
Hi Chendong,
You have a cool project. Are you just looking into radiation therapy scheduling calculation?
I was just curious if in your dataset, there was any data points on people who missed/rescheduled/delays with their appointment that could become another variable for your calculation. As sometimes there are unforeseen factors (i.e. sudden shortage of doctors or therapy materials) that may result in delayed therapy appointment contributing to increasing wait time for an appointment.
Hi Grace,
Really sorry for the late reply.
Yes, my intention is to provide a patient-specific algorithm to make the scheduling more precise.
In the dataset I used, there is only one patient missing with one fraction of treatment. As to the rescheduling and delayed cases, I believe they exist in real world but the data I have just show the treatment time of each fraction of RT, which don’t have specific date or other indicators reflecting the rescheduling or delaying.
You just suggested a very very good idea that these delay/rescheduling could be a latent factor not shown in the dataset but definitely have influence on the scheduling tool. That could be the next research problem that I will look into.
Thank you so much for providing these comments and hope I answer your questions.