Predictive Solution for Radiation Toxicity Based on Big Data

Abstract

Radiotherapy is a treatment method using radiation for cancer treatment based on a patient treatment planning for each radiotherapy machine. At this time, the dose, volume, device setting information, complication, tumor control probability, etc. are considered as a single-patient treatment for each fraction during radiotherapy process. Thus, these filed-up big data for a long time and numerous patients' cases are inevitably suitable to produce optimal treatment and minimize the radiation toxicity and complication. Thus, we are going to handle up prostate, lung, head, and neck cancer cases using machine learning algorithm in radiation oncology. And, the promising algorithms as the support vector machine, decision tree, and neural network, etc. will be introduced in machine learning. In conclusion, we explain a predictive solution of radiation toxicity based on the big data as treatment planning decision support system.

Prediction of Cancer Patient Outcomes Based on Artificial Intelligence

“…Decision support systems for treatment planning have integrated imaging, dosimetry, biological, and other data in a quantitative manner to provide specific clinical predictions [13]. For example, a treatment planning decision support system that predicts radiation toxicity based on big data now exists [14]. Importantly, validation and standardization are crucial when developing medical decision support systems [15,16].…”