49 citations · 113 across the 23 of their papers we have counts for
8 papers · 2 filters
Investigating Large Language Models and Control Mechanisms to Improve Text Readability of Biomedical Abstracts
Zihao Li, Samuel Belkadi, Nicolo Micheletti +3
Biomedical literature often uses complex language and inaccessible professional terminologies. That is why simplification plays an important role in improving public health literac…
MC-DRE: Multi-Aspect Cross Integration for Drug Event/Entity Extraction
Jie Yang, Soyeon Caren Han, Siqu Long +2
Extracting meaningful drug-related information chunks, such as adverse drug events (ADE), is crucial for preventing morbidity and saving many lives. Most ADEs are reported via an u…
MedMine: Examining Pre-trained Language Models on Medication Mining
Haifa Alrdahi, Lifeng Han, Hendrik Šuvalov +1
Automatic medication mining from clinical and biomedical text has become a popular topic due to its real impact on healthcare applications and the recent development of powerful la…
PULSAR at MEDIQA-Sum 2023: Large Language Models Augmented by Synthetic Dialogue Convert Patient Dialogues to Medical Records
Viktor Schlegel, Hao Li, Yuping Wu +8
This paper describes PULSAR, our system submission at the ImageClef 2023 MediQA-Sum task on summarising patient-doctor dialogues into clinical records. The proposed framework relie…
PULSAR: Pre-training with Extracted Healthcare Terms for Summarising Patients' Problems and Data Augmentation with Black-box Large Language Models
Hao Li, Yuping Wu, Viktor Schlegel +7
Medical progress notes play a crucial role in documenting a patient's hospital journey, including his or her condition, treatment plan, and any updates for healthcare providers. Au…
Do You Hear The People Sing? Key Point Analysis via Iterative Clustering and Abstractive Summarisation
Hao Li, Viktor Schlegel, Riza Batista-Navarro +1
Argument summarisation is a promising but currently under-explored field. Recent work has aimed to provide textual summaries in the form of concise and salient short texts, i.e., k…