xMEN: a modular toolkit for cross-lingual medical entity normalization.

Objective: To improve performance of medical entity normalization across many languages, especially when fewer language resources are available compared to English.

Materials And Methods: We propose xMEN, a modular system for cross-lingual (x) medical entity normalization (MEN), accommodating both low- and high-resource scenarios. To account for the scarcity of aliases for many target languages and terminologies, we leverage multilingual aliases via cross-lingual candidate generation.

Late-Onset Femoroacetabular Impingement Syndrome Following Knee Arthroscopy in a Retrospective Cohort.

Hip-knee coupling is a well-documented phenomenon, and interventions to one joint can alter biomechanics at the other. The purpose of this study was to investigate if knee surgery is associated with later onset of femoroacetabular impingement syndrome (FAIS). A retrospective chart review was conducted regarding patients at a single academic institution who underwent hip arthroscopy for FAIS between January 2011-October 2021.

Unsupervised SapBERT-based bi-encoders for medical concept annotation of clinical narratives with SNOMED CT.

Objective: Clinical narratives provide comprehensive patient information. Achieving interoperability involves mapping relevant details to standardized medical vocabularies. Typically, natural language processing divides this task into named entity recognition (NER) and medical concept normalization (MCN).

Prospectively investigating the impact of AI onshared decision-making in post kidney transplant care (PRIMA-AI): protocol for a longitudinal qualitative study among patients, their support persons and treating physicians at a tertiary care centre.

Introduction: As healthcare is shifting from a paternalistic to a patient-centred approach, medical decision making becomes more collaborative involving patients, their support persons (SPs) and physicians. Implementing shared decision-making (SDM) into clinical practice can be challenging and becomes even more complex with the introduction of artificial intelligence (AI) as a potential actant in the communicative network. Although there is more empirical research on patients' and physicians' perceptions of AI, little is known about the impact of AI on SDM.

Synovial Fluid Biomarker Alternatives Can Plasma and Urine Samples Shed Light on the Post-Traumatic Intra-Articular Microenvironment?

The purpose of this study was to analyze the relationship between the intra-articular inflammatory response and any associated systemic inflammatory response following knee injury requiring operative management. Patients undergoing primary knee arthroscopy provided synovial fluid, blood, and urine samples immediately prior to surgery. Samples were analyzed using a multiplex magnetic bead immunoassay for the concentrations of cytokines and growth factors that have been shown to be associated with post-injury inflammation.