Discontinuous named entities in clinical Text: A systematic literature review.

Objective: Extracting named entities from clinical free-text presents unique challenges, particularly when dealing with discontinuous entities-mentions that are separated by unrelated words. Traditional NER methods often struggle to accurately identify these entities, prompting the development of specialised computational solutions. This paper systematically reviews and presents the methodologies developed for Discontinuous Named Entity Recognition in clinical texts, highlighting their effectiveness and the challenges they face.

From outputs to insights: a survey of rationalization approaches for explainable text classification.

Deep learning models have achieved state-of-the-art performance for text classification in the last two decades. However, this has come at the expense of models becoming less understandable, limiting their application scope in high-stakes domains. The increased interest in explainability has resulted in many proposed forms of explanation.

Barriers and facilitators to the HPV vaccine: a multicenter qualitative study of French general practitioners.

Background: In France, human papillomavirus (HPV) vaccination coverage is low, with 30.7% of 17-year-old girls having received a complete HPV vaccination schedule in 2020.

Aim: To determine the perspective and behaviors of general practitioners (GPs) regarding HPV vaccination with their patients and if a reluctance is observed.

PrEP in the Context of Other HIV Risk Reduction Strategies Among Men Who Have Sex with Men: Results from the Flash! PrEP in Europe Survey.

Combination HIV prevention covers a range of biomedical, behavioral, and socio-structural interventions. Despite the growing availability of pre-exposure prophylaxis (PrEP), it is not always accessible in European Centre for Disease Prevention and Control reporting countries and may not meet the needs of all at-risk populations. Based on the Flash! PrEP in Europe data, multiple correspondence analysis and hierarchical clustering were used to identify patterns in HIV prevention strategies among 9980 men who have sex with men (MSM).