BACKGROUND: To evaluate the impact of an annotation guideline on the performance of large language models (LLMs) in extracting data from stroke computed tomography (CT) reports.
Anais da Academia Brasileira de Ciencias
Jun 16, 2025
This research focuses on predicting cardiovascular disease using machine learning classification strategies. The study presents a unique approach by integrating multiple machine learning techniques, leveraging the strengths of Random Forest and Gradi...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Jun 11, 2025
BACKGROUND: Delayed or missed stroke diagnosis is associated with poor outcomes. We utilized natural language processing of notes from non-neurological emergency department (ED) encounters to identify text phrases indicating stroke presentations that...
Difficult-to-treat depression (DTD) has been proposed as a broader and more clinically comprehensive perspective on a person's depressive disorder where, despite treatment, they continue to experience significant burden. We sought to develop a tool c...
Systematic literature review (SLR) is an important tool for Health Economics and Outcomes Research (HEOR) evidence synthesis. SLRs involve the identification and selection of pertinent publications and extraction of relevant data elements from full-t...
Drug-target interactions (DTIs) play a critical role in drug discovery and repurposing. Deep learning-based methods for predicting drug-target interactions are more efficient than wet-lab experiments. The extraction of original and substructural feat...
The techniques used in yoga have roots in traditions that precede modern science. Research shows that yoga enhances quality of life and well-being, positively impacting physical and mental health. As yoga gains acceptance in Western countries, scient...
Electronic Health Records (EHRs) contain written notes by all kinds of medical professionals about all aspects of well-being of a patient. When adequately processed with a Large Language Model (LLM), this enormous source of information can be analyze...
BACKGROUND: Screening and surveillance are essential to prevent aneurysm rupture. We used natural language processing (NLP) software to evaluate efficacy of aneurysm surveillance.
Feature selection is a crucial preprocessing step in the fields of machine learning, data mining and pattern recognition. In medical data analysis, the large number and complexity of features are often accompanied by redundant or irrelevant features,...
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