BACKGROUND: Ireland is ranked among the most disadvantageous European countries in terms of mental health challenges. Contrary to general health services that primarily focus on diagnosis and treatment, the mental health sector in Ireland deals with ...
International journal of medical informatics
Jun 23, 2025
BACKGROUND: Traditional Electronic Health Record (EHR) data analysis at King's College Hospital relies on extensive manual effort, from data extraction to reporting, limiting efficiency and scalability. This study presents an automated framework for ...
The healthcare sector increasingly relies on Electronic Health Records (EHRs) for efficient and high-quality patient care by providing rapid access to comprehensive medical information. However, these records contain sensitive patient data that must ...
Automatic phenotype extraction and assertion negation detection from large-scale accessible Electronic Health Records (EHRs), including discharge summaries and radiology reports, is a crucial task for various healthcare applications, such as disease ...
International journal of medical informatics
Jun 21, 2025
BACKGROUND: Patients with rare diseases frequently experience misdiagnoses and long diagnostic delays. Accelerating their diagnosis is essential to ensure timely access to appropriate care. Given the increasing availability of EHRs, combining artific...
Medication prescriptions in electronic health records (EHR) are often in free-text and may include a mix of languages, local brand names, and a wide range of idiosyncratic formats and abbreviations. Large language models (LLMs) have shown a promising...
OBJECTIVE: Generating discharge summaries is a crucial yet time-consuming task in clinical practice, essential for conveying pertinent patient information and facilitating continuity of care. Recent advancements in large language models (LLMs) have s...
Understanding acute heart failure (AHF) remains a significant challenge, as many clinical details are recorded in unstructured text rather than structured data in electronic health records (EHRs). In this study, we explored the use of large language ...
BACKGROUND: Machine learning (ML) and big data analytics are rapidly transforming health care, particularly disease prediction, management, and personalized care. With the increasing availability of real-world data (RWD) from diverse sources, such as...
BACKGROUND: Colorectal cancer is now the leading cause of cancer-related deaths among young Americans. Accurate early prediction and a thorough understanding of the risk factors for early-onset colorectal cancer (EOCRC) are vital for effective preven...
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