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View article: Will large language models transform clinical prediction?
Will large language models transform clinical prediction? Open
Further work and interdisciplinary collaboration are needed to support equitable and effective integration into the clinical prediction. Developing temporally aware, fair, and explainable models should be a priority focus for transforming …
View article: Investigating Social Media Use by Young People to Self-Manage Type 1 Diabetes Mellitus: Large-Scale Analysis of Social Media Discussions Using Topic Modeling
Investigating Social Media Use by Young People to Self-Manage Type 1 Diabetes Mellitus: Large-Scale Analysis of Social Media Discussions Using Topic Modeling Open
Background Social media has shown promise in supporting young people with type 1 diabetes mellitus (T1DM) by providing information and emotional support. Although previous qualitative studies have investigated young people’s self-reported …
View article: Term2Note: Synthesising Differentially Private Clinical Notes from Medical Terms
Term2Note: Synthesising Differentially Private Clinical Notes from Medical Terms Open
Training data is fundamental to the success of modern machine learning models, yet in high-stakes domains such as healthcare, the use of real-world training data is severely constrained by concerns over privacy leakage. A promising solutio…
View article: Structured Information Matters: Explainable ICD Coding with Patient-Level Knowledge Graphs
Structured Information Matters: Explainable ICD Coding with Patient-Level Knowledge Graphs Open
Mapping clinical documents to standardised clinical vocabularies is an important task, as it provides structured data for information retrieval and analysis, which is essential to clinical research, hospital administration and improving pa…
View article: Evaluating Differentially Private Generation of Domain-Specific Text
Evaluating Differentially Private Generation of Domain-Specific Text Open
Generative AI offers transformative potential for high-stakes domains such as healthcare and finance, yet privacy and regulatory barriers hinder the use of real-world data. To address this, differentially private synthetic data generation …
View article: Exploring the consistency, quality and challenges in manual and automated coding of free-text diagnoses from hospital outpatient letters
Exploring the consistency, quality and challenges in manual and automated coding of free-text diagnoses from hospital outpatient letters Open
Clinical coding is the process of extracting key information contained within clinical free-text and representing this information using standardised clinical terminologies. In doing so, unstructured text is transformed into structured dat…
View article: Generative Models and Sentence Transformers for the Recognition and Normalization of Continuous and Discontinuous Phenotype Mentions: Model Development and Evaluation
Generative Models and Sentence Transformers for the Recognition and Normalization of Continuous and Discontinuous Phenotype Mentions: Model Development and Evaluation Open
Background Extracting genetic phenotype mentions from clinical reports and normalizing them to standardized concepts within the human phenotype ontology are essential for consistent interpretation and representation of genetic conditions. …
View article: Arg-LLaDA: Argument Summarization via Large Language Diffusion Models and Sufficiency-Aware Refinement
Arg-LLaDA: Argument Summarization via Large Language Diffusion Models and Sufficiency-Aware Refinement Open
Argument summarization aims to generate concise, structured representations of complex, multi-perspective debates. While recent work has advanced the identification and clustering of argumentative components, the generation stage remains u…
View article: Development and validation of prediction models for predicting social care strengths and vulnerability in older people: Cohort study using routine data in Adult Social Care
Development and validation of prediction models for predicting social care strengths and vulnerability in older people: Cohort study using routine data in Adult Social Care Open
In Adult Social Care, UK local authorities have statutory responsibilities for assessing needs and delivering services to ensure adults’ wellbeing. Administrative data collected during this process may help local authorities’ compliance wi…
View article: Large Language Models in Argument Mining: A Survey
Large Language Models in Argument Mining: A Survey Open
Large Language Models (LLMs) have fundamentally reshaped Argument Mining (AM), shifting it from a pipeline of supervised, task-specific classifiers to a spectrum of prompt-driven, retrieval-augmented, and reasoning-oriented paradigms. Yet …
View article: Synthetic4Health: generating annotated synthetic clinical letters
Synthetic4Health: generating annotated synthetic clinical letters Open
Clinical letters contain sensitive information, limiting their use in model training, medical research, and education. This study aims to generate reliable, diverse, and de-identified synthetic clinical letters to support these tasks. We i…
View article: Will Large Language Models Transform Clinical Prediction?
Will Large Language Models Transform Clinical Prediction? Open
Objective: Large language models (LLMs) are attracting increasing interest in healthcare. This commentary evaluates the potential of LLMs to improve clinical prediction models (CPMs) for diagnostic and prognostic tasks, with a focus on the…
View article: Data, dialogue, and design: patient and public involvement and engagement for natural language processing with real-world cancer data
Data, dialogue, and design: patient and public involvement and engagement for natural language processing with real-world cancer data Open
Introduction This study describes the process and outcomes of a Patient and Public Involvement and Engagement (PPIE) event designed to incorporate patient perspectives into the application of Natural Language Processing (NLP) for analyzing…
View article: Automatic genetic phenotype normalization from dysmorphology physical examinations: an overview of the BioCreative VIII—Task 3 competition
Automatic genetic phenotype normalization from dysmorphology physical examinations: an overview of the BioCreative VIII—Task 3 competition Open
We present here an overview of the BioCreative VIII Task 3 competition, which called for the development of state-of-the-art approaches to automatic normalization of observations noted by physicians in dysmorphology physical examinations t…
View article: MaLei at the PLABA Track of TREC 2024: RoBERTa for Term Replacement -- LLaMA3.1 and GPT-4o for Complete Abstract Adaptation
MaLei at the PLABA Track of TREC 2024: RoBERTa for Term Replacement -- LLaMA3.1 and GPT-4o for Complete Abstract Adaptation Open
This report is the system description of the MaLei team (Manchester and Leiden) for the shared task Plain Language Adaptation of Biomedical Abstracts (PLABA) 2024 (we had an earlier name BeeManc following last year), affiliated with TREC20…
View article: Generative Models and Sentence Transformers for the Recognition and Normalization of Continuous and Discontinuous Phenotype Mentions: Model Development and Evaluation (Preprint)
Generative Models and Sentence Transformers for the Recognition and Normalization of Continuous and Discontinuous Phenotype Mentions: Model Development and Evaluation (Preprint) Open
BACKGROUND Extracting genetic phenotype mentions from clinical reports and normalizing them to standardized concepts within the human phenotype ontology are essential for consistent interpretation and representation of genetic conditions.…
View article: TriG-NER: Triplet-Grid Framework for Discontinuous Named Entity Recognition
TriG-NER: Triplet-Grid Framework for Discontinuous Named Entity Recognition Open
Discontinuous Named Entity Recognition (DNER) presents a challenging problem where entities may be scattered across multiple non-adjacent tokens, making traditional sequence labelling approaches inadequate. Existing methods predominantly r…
View article: CAST: Corpus-Aware Self-similarity Enhanced Topic modelling
CAST: Corpus-Aware Self-similarity Enhanced Topic modelling Open
Topic modelling is a pivotal unsupervised machine learning technique for extracting valuable insights from large document collections. Existing neural topic modelling methods often encode contextual information of documents, while ignoring…