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Electronic Health Records

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Development and validation of electronic health record-based, machine learning algorithms to predict quality of life among family practice patients.

Scientific reports
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
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
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
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
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
OBJECTIVE: To assess the quality of artificial intelligence (AI) scribes and to evaluate their impact on urologic practice.

Fair and explainable Myocardial Infarction (MI) prediction: Novel strategies for feature selection and class imbalance correction.

Computers in biology and medicine
The rising incidences of myocardial infarction (MI), often affecting individuals without traditional risk factors, highlight the urgent need for improved early detection using personal health data. However, health surveys and electronic health record...

Developing a prediction model for cognitive impairment in older adults following critical illness.

BMC geriatrics
BACKGROUND: New or worsening cognitive impairment or dementia is common in older adults following an episode of critical illness, and screening post-discharge is recommended for those at increased risk. There is a need for prediction models of post-I...

Development and validation of a rheumatoid arthritis case definition: a machine learning approach using data from primary care electronic medical records.

BMC medical informatics and decision making
BACKGROUND: Rheumatoid Arthritis (RA) is a chronic inflammatory disease that is primarily diagnosed and managed by rheumatologists; however, it is often primary care providers who first encounter RA-related symptoms. This study developed and validate...

Large Language Models to Identify Advance Care Planning in Patients With Advanced Cancer.

Journal of pain and symptom management
CONTEXT: Efficiently tracking Advance Care Planning (ACP) documentation in electronic heath records (EHRs) is essential for quality improvement and research efforts. The use of large language models (LLMs) offers a novel approach to this task.