AIMC Topic: Electronic Health Records
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Contextualized race and ethnicity annotations for clinical text from MIMIC-III.
Scientific data
Dec 5, 2024
Observational health research often relies on accurate and complete race and ethnicity (RE) patient information, such as characterizing cohorts, assessing quality/performance metrics of hospitals and health systems, and identifying health disparities...
CALLM: Enhancing Clinical Interview Analysis Through Data Augmentation With Large Language Models.
IEEE journal of biomedical and health informatics
Dec 5, 2024
The global prevalence of mental health disorders is increasing, leading to a significant economic burden estimated in trillions of dollars. In automated mental health diagnosis, the scarcity and imbalance of clinical data pose considerable challenges...
Automated derivation of diagnostic criteria for lung cancer using natural language processing on electronic health records: a pilot study.
BMC medical informatics and decision making
Dec 4, 2024
BACKGROUND: The digitisation of healthcare records has generated vast amounts of unstructured data, presenting opportunities for improvements in disease diagnosis when clinical coding falls short, such as in the recording of patient symptoms. This st...
Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions.
BMJ health & care informatics
Dec 4, 2024
OBJECTIVES: Increasing operational pressures on emergency departments (ED) make it imperative to quickly and accurately identify patients requiring urgent clinical intervention. The widespread adoption of electronic health records (EHR) makes rich fe...
Development and validation of electronic health record-based, machine learning algorithms to predict quality of life among family practice patients.
Scientific reports
Dec 3, 2024
Health-related quality of life (HRQol) is a crucial dimension of care outcomes. Many HRQoL measures exist, but methodological and implementation challenges impede primary care (PC) use. We aim to develop and evaluate a novel machine learning (ML) alg...
A novel deep learning algorithm for real-time prediction of clinical deterioration in the emergency department for a multimodal clinical decision support system.
Scientific reports
Dec 3, 2024
The array of complex and evolving patient data has limited clinical decision making in the emergency department (ED). This study introduces an advanced deep learning algorithm designed to enhance real-time prediction accuracy for integration into a n...
Enhancing suicidal behavior detection in EHRs: A multi-label NLP framework with transformer models and semantic retrieval-based annotation.
Journal of biomedical informatics
Dec 2, 2024
BACKGROUND: Suicide is a leading cause of death worldwide, making early identification of suicidal behaviors crucial for clinicians. Current Natural Language Processing (NLP) approaches for identifying suicidal behaviors in Electronic Health Records ...
PhraseAug: An Augmented Medical Report Generation Model With Phrasebook.
IEEE transactions on medical imaging
Dec 2, 2024
Medical report generation is a valuable and challenging task, which automatically generates accurate and fluent diagnostic reports for medical images, reducing workload of radiologists and improving efficiency of disease diagnosis. Fine-grained align...
Predicting the physiological effects of multiple drugs using electronic health record.
Computers in biology and medicine
Dec 1, 2024
Various computational models have been developed to understand the physiological effects of drug-drug interactions, which can contribute to more effective drug treatments. However, they mostly focus on interactions of only two drugs, and do not consi...
Assessing the Efficacy and Clinical Utility of Artificial Intelligence Scribes in Urology.
Urology
Nov 30, 2024
OBJECTIVE: To assess the quality of artificial intelligence (AI) scribes and to evaluate their impact on urologic practice.
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