Hierarchical embedding attention for overall survival prediction in lung cancer from unstructured EHRs - Paolo, Domenico; Greco, Carlo; Cortellini, Alessio; Ramella, Sara; Soda, Paolo; Bria, Alessandro; Sicilia, Rosa (BMC medical informatics and decision making, 2025)
Keywords: Attention mechanism; Automation; Carcinoma, Non-Small-Cell Lung - mortality; Cell survival; Decision making; Deep learning; Effectiveness; Electronic health records; Electronic Health Records - statistics & numerical data; Electronic medical records; Electronic records; Embedding; Feature extraction; Female; Health aspects; Health Informatics; Humans; Information processing; Information Systems and Communication Service; Lung cancer; Lung cancer, Non-small cell; Lung Neoplasms - mortality; Male; Management of Computing and Information Systems; Medical history; Medical prognosis; Medical records; Medicine; Medicine & Public Health; Methods; Natural Language Processing; Natural language processing in medical informatics; NER; Non-small cell lung carcinoma; Patient outcomes; Patients; Prediction models; Prognosis; Representations; Small cell lung carcinoma; Statistical analysis; Statistical models; Subject specialists; Survival; Survival Analysis; Transformer; Unstructured data; Unstructured EHRs; Italy; Attention mechanism; Survival analysis; NER; Unstructured EHRs; Transformer; Lung cancer