Predicting patient survival after TACE for HCC using a neural network: A promising tool

This repository enables external validation of the artificial neural network published in https://doi.org/... using the pretrained neural network as described in the manuscript. The parameters included in the model are: Demographics - gender = 'MALE' or 'FEMALE' - bclc = Barcelona Clinic Liver Cancer staging system (values: 0, A, B, C, D) - age = age at second TACE, in years Etiology / concomitant disease - nicotine, obesity, diabetes, etiology_alcohol (in case of liver cirrhosis due to alcohol abuse), etiology_hbv (in case of liver cirrhosis due to chronic hepatitis B infection), etiology_hcv (in case of liver cirrhosis due to chronic hepatitis C infection), and etiology_unknown (in case of liver cirrhosis of unknown etiology). All these parameters can take values: 0 = false and 1 = true Tumor related - baseline_tumornumber = number of tumor lesions at baseline - baseline_diffuse_tumor = diffuse tumor growth pattern (values: 0 = nodular pattern and 1 = diffuse pattern) - mRECIST_1st, mRECIST_2nd: mRECIST evaluation of cross-sectional imaging prior to first and prior to second TACE - response: radiological response after first TACE (values: 0 = false and 1 = true) Laboratory / liver function - natrium_1st, natrium_2nd, bilirubin_1st, bilirubin_2nd, albumin_1st, albumin_2nd, got_1st, got_2nd, gpt_1st, gpt_2nd, inr_1st, inr_2nd, thrombocytes_1st, thrombocytes_2nd, afp_1st, afp_2nd: laboratory values prior to first and prior to second TACE - child_score_1st, child_score_2nd, meld_1st, meld_2nd: Child Pugh and MELD score prior to first and prior to second TACE Sarcopenia - smi_1st, smi_2nd: skeletal muscle index/psoas muscle index measured at the level of the L3 vertebrae prior to first and prior to second TAC