Furthermore, we compared the ML/DL modeling methods and found that the CNN-TL&DA, which combined molecular images (MI), achieved the best overall performance (R2test = 0.896, RMSEtest = 0.362, MAEtest = 0.261) when compared to the XGBoost algorithm combined with Mordred descriptors (MD) (0.692, RMSEtest = 0.622, MAEtest = 0.399) and Morgan fingerprint (MF) (R2test = 0.512, RMSEtest = 0.783, MAEtest = 0.520). 
THERM