AIMC Topic: Electronic Health Records

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Predicting 30-Days Hospital Readmission for Patients with Heart Failure Using Electronic Health Record Embeddings: Comparative Evaluation.

JMIR medical informatics
BACKGROUND: Heart failure (HF) is a public health concern with a wider impact on quality of life and cost of care. One of the major challenges in HF is the higher rate of unplanned readmissions and suboptimal performance of models to predict the read...

Leveraging Machine Learning and Robotic Process Automation to Identify and Convert Unstructured Colonoscopy Results Into Actionable Data: Proof-of-Concept Study.

JMIR medical informatics
BACKGROUND: With rising patient volumes and a focus on quality, our health system had the objective to create a more efficient way to ensure accurate documentation of colorectal cancer (CRC) screening intervals from inbound colonoscopy reports to ens...

Methods for Addressing Missingness in Electronic Health Record Data for Clinical Prediction Models: Comparative Evaluation.

JMIR medical informatics
BACKGROUND: Missing data are a common challenge in electronic health record (EHR)-based prediction modeling. Traditional imputation methods may not suit prediction or machine learning models, and real-world use requires workflows that are implementab...

Named Entity Recognition for Chinese Cancer Electronic Health Records-Development and Evaluation of a Domain-Specific BERT Model: Quantitative Study.

JMIR medical informatics
BACKGROUND: The unstructured data of Chinese cancer electronic health records (EHRs) contains valuable medical expertise. Accurate medical entity recognition is crucial for building a medical-assisted decision system. Named entity recognition (NER) i...

Predicting 30-day and 1-year mortality in heart failure with preserved ejection fraction (HFpEF).

PloS one
OBJECTIVES: To develop and compare prediction models for 30-day and 1-year mortality in Heart failure with preserved ejection fraction (HFpEF) using EHR data, utilizing both traditional and machine learning (ML) techniques.

Process for Quality Management of Electronic Medical Records-Based Data: Case Study Using Real Colorectal Cancer Data.

JMIR medical informatics
BACKGROUND: As data-driven medical research advances, vast amounts of medical data are being collected, giving researchers access to important information. However, issues such as heterogeneity, complexity, and incompleteness of datasets limit their ...

Estimating 10-Year Cardiovascular Disease Risk in Primary Prevention Using UK Electronic Health Records and a Hybrid Multitask BERT Model: Retrospective Cohort Study.

JMIR medical informatics
BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of preventable morbidity and mortality, highlighting the need for early risk stratification in primary prevention. Traditional Cox models assume proportional hazards and linear effects,...

AI-generated neurology consultation summaries improve efficiency and reduce documentation burden in the emergency department.

Scientific reports
Physicians face a significant documentation burden, spending twice as much time on electronic health records (EHRs) as on direct patient care. Consultation summary reports from the emergency department (ED) are critical for continuity of care and cli...

A large language model for delirium prediction in the intensive care unit using structured electronic health records.

Scientific reports
Delirium is an acute syndrome characterized by fluctuating attention, cognitive impairment, and severe disorganization of behavior, which has been shown to affect up to 31% of patients in the intensive care unit (ICU). Early detection can enable time...