An Algorithm for Optimizing Anticancer Treatment

In the past few decades, many anticancer drugs were discovered and developed, nowadays, the newer chemotherapeutic agents were being continually introduced. This is good news for cancer patients, but it puts a much burden on the physician. It is difficult for physicians to recommend drugs with the best efficacy for cancer patients with long experience. Therefore, an algorithm that recommends optimal drugs is needed. It is the best drug to have good sensitivity and low resistance to cancer patients. Algorithm should be designed based on Big Data about sensitivity correlation coefficient and resistance correlation coefficient. For optimal drug prediction, it is necessary to go through several complex layers. The DBN model is more suitable than the ANN model.