Continual learning has emerged as a powerful approach to address the challenges of non-
stationary environments, allowing machine learning models to adapt to new data while …

Abstract Medical Concept Normalization (MCN) is a crucial process for deep information
extraction and natural language processing tasks, which plays a vital role in biomedical …

Hypothesis generation (HG) is a fundamental prob-lem in biomedical text mining that
uncovers plausible implicit links (B terms) between two disjoint concepts of interest (A and C …

Interpreting patient case descriptions has emerged as a challenging problem for biomedical
NLP, where the aim is typically to predict diagnoses, to recommended treatments, or to …

The advent of pre-trained language models (LMs) has enabled unprecedented advances in
the Natural Language Processing (NLP) field. In this respect, various specialised LMs for the …

Recent progress in biological, medical and health-care technologies, and innovations in
wearable sensors provide us with unprecedented opportunities to accumulate massive data …