Thus, the output value can be interpreted as probability of inhibition according to the deep-learning model. The compound with the highest probability of inhibition (0.99) is doxorubicin, which also has a strong docking score of -7.91, making it a promising candidate. Table lists the top 100 drug candidates ranked by a combination of their docking score rank and deep-learning-predicted rank. Although ranking by docking scores (Table ) is the most reliable, combining these two ranking methods can present a more comprehensive picture of the best candidates. For example, ibrutinib, acalabrutinib, and hesperidin, are the top two candidates by this join scaling measure, with combined ranks of 10, 13, and 15, respectively. The fact that these compounds' incredibly high-performing docking scores are backed by the deep-learning model makes them some of the most promising candidates. b