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A comprehensive benchmarking for evaluating TCR embeddings in modeling TCR-epitope interactions.
Brief Bioinform
November 2024
Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon Tong, Hong Kong, 999077, China.
The complexity of T cell receptor (TCR) sequences, particularly within the complementarity-determining region 3 (CDR3), requires efficient embedding methods for applying machine learning to immunology. While various TCR CDR3 embedding strategies have been proposed, the absence of their systematic evaluations created perplexity in the community. Here, we extracted CDR3 embedding models from 19 existing methods and benchmarked these models with four curated datasets by accessing their impact on the performance of TCR downstream tasks, including TCR-epitope binding affinity prediction, epitope-specific TCR identification, TCR clustering, and visualization analysis.
View Article and Find Full Text PDFUsing Large Language Models to Detect and Understand Drug Discontinuation Events in Web-Based Forums: Development and Validation Study.
J Med Internet Res
January 2025
Department of Industrial and Systems Engineering, The University of Florida, GAINESVILLE, FL, United States.
Background: The implementation of large language models (LLMs), such as BART (Bidirectional and Auto-Regressive Transformers) and GPT-4, has revolutionized the extraction of insights from unstructured text. These advancements have expanded into health care, allowing analysis of social media for public health insights. However, the detection of drug discontinuation events (DDEs) remains underexplored.
View Article and Find Full Text PDFStudying gender in the experiences of patients with heart failure: A scoping review of qualitative studies and methodological recommendations.
Womens Health (Lond)
January 2025
Department of Ethics Law and Humanities, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands.
Background: Considering how gendered experiences play a role in the lives of patients with heart failure (HF) is critical in order to understand their experiences, optimise clinical care and reduce health inequalities.
Objectives: The aim of our study was to review how gender is being studied in qualitative research in HF, specifically to (1) analyse how gender is conceptualised and applied in qualitative HF research; and (2) identify methodological opportunities to better understand the gendered experiences of patients with HF.
Eligibility Criteria: We conducted a systematic search of literature, including qualitive or mixed-methods articles focussing on patients' perspectives in HF and using gender as a primary analytical factor, excluding articles published before 2000.
A new HCM heart sound classification method based on weighted bispectrum features.
Phys Eng Sci Med
January 2025
School of Electrical Engineering and Electronic Information, Xihua University, Chengdu, China.
Hypertrophic cardiomyopathy (HCM), including obstructive HCM and non-obstructive HCM, can lead to sudden cardiac arrest in adolescents and athletes. Early diagnosis and treatment through auscultation of different types of HCM can prevent the occurrence of malignant events. However, it is challenging to distinguish the pathological information of HCM related to differential left ventricular outflow tract pressure gradients.
View Article and Find Full Text PDFGraph convolution network-based eeg signal analysis: a review.
Med Biol Eng Comput
January 2025
School of Control Science and Engineering, Tiangong University, Tianjin, 300387, China.
With the advancement of artificial intelligence technology, more and more effective methods are being used to identify and classify Electroencephalography (EEG) signals to address challenges in healthcare and brain-computer interface fields. The applications and major achievements of Graph Convolution Network (GCN) techniques in EEG signal analysis are reviewed in this paper. Through an exhaustive search of the published literature, a module-by-module discussion is carried out for the first time to address the current research status of GCN.
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