We are very happy that Professor Sophia Ananiadou will give an invited talk at the eleventh BioASQ workshop.
Title: Biomedical Text Summarisation: methods, challenges, and future directions
Speaker: Sophia Ananiadou, The University of Manchester.
Abstract: Biomedical text summarisation (BTS) methods are used to generate concise summaries that distill key information from either single or multiple biomedical documents. The development of pre-trained language models and recently large language models have changed the BTS research landscape, through the emergence of numerous novel summarisation methods, datasets and evaluation metrics. We will examine the challenges encountered in biomedical text summarization, delve into our approaches, in particular the incorporation of domain specific knowledge into models, evaluation efforts (readability and factuality) and discuss future directions of BTS in the era of large language models.
Biosketch: Sophia Ananiadou is Professor in Computer Science at The University of Manchester. Her main areas of research are Natural Language Processing and Biomedical Text Mining. She is the Director of the UK National Centre for Text Mining, Deputy Director of the Institute of Data Science and AI (Manchester), Turing Fellow, ELLIS member, and Distinguished research fellow at the AI research centre (AIST Japan). Following a Bachelors in Linguistics, University of Athens, she obtained 2 Masters from Paris Universities (Linguistics, Jussieu; Literature, Sorbonne, and a PhD in Natural Language Processing, University of Manchester Institute of Science and Technology. Her research interests evolved on how AI systems could acquire and exploit knowledge of language, particularly in specialised domains. She became involved in interdisciplinary research and played a leading role in bridging text mining to systems biology, bioinformatics, public health but also humanities and law. She deepened her research into automatic term recognition, the design and construction of large-scale linguistic resources (annotated text corpora, computational lexicons), information extraction, semantic search, emotion detection, text summarisation and simplification. Since 2002, she is co-instigator of a Special Interest Group within ACL (SIGBioMed) dedicated to language processing in the biological, biomedical, and clinical domain bringing together researchers in NLP, bioinformatics, and medical informatics.
