AIMC Topic: Electronic Health Records

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Explainable AI for infection prevention and control: modeling CPE acquisition and patient outcomes in an Irish hospital with transformers.

BMC medical informatics and decision making
BACKGROUND: Carbapenemase-Producing Enterobacteriace (CPE) poses a critical concern for infection prevention and control in hospitals. However, predictive modeling of previously highlighted CPE-associated risks such as readmission, mortality, and ext...

Machine learning for sudden cardiac death prediction among older adults using community-based electronic health records.

BMC public health
BACKGROUND: Machine learning (ML) models have shown good performance in predicting cardiovascular disease risk. However, the usefulness of ML models has yet to be fully elucidated for sudden cardiac death (SCD) risk using long-term follow-up electron...

Burden and risk factors of depression in seniors from 1990 to 2021: a multi-database study based on EMR mining methods.

Translational psychiatry
Depression in seniors is a growing public health concern worldwide. Despite the rising prevalence of depression in this demographic, comprehensive data on its burden and trends over an extended period remain limited. This study aims to assess the tre...

Implementation of a Digital Health Intervention (CHAMP) for Self-Monitoring of Hypertension: Protocol for 3 Interlinked Implementation Studies.

JMIR research protocols
BACKGROUND: Hypertension affects 31% of the global adult population. Artificial intelligence-based chatbots may support self-management of hypertension and other chronic disorders. Chronic Disease Management Program (CHAMP) is a digital health interv...

Clinical Information Extraction From Notes of Veterans With Lymphoid Malignancies: Natural Language Processing Study.

JMIR medical informatics
BACKGROUND: Clinical natural language processing (cNLP) techniques are commonly developed and used to extract information from clinical notes to facilitate clinical decision-making and research. However, they are less established for rare diseases su...

Predicting All-Cause Mortality in Diabetic Patients 2 Years in Advance Using Aggregated EHR Data and Machine Learning.

Journal of medical systems
This study presents a machine learning-driven model predicting all-cause mortality two years in advance using administrative health data focused on diabetic patients. Integrating hospitalization records, emergency department data, demographics, and c...

Automated Chronic Obstructive Pulmonary Disease Phenotyping and Control Assessment in Primary Care: Retrospective Multicenter Study Using the Seleida Model.

JMIR medical informatics
BACKGROUND: Chronic obstructive pulmonary disease (COPD) remains a leading global health burden. In primary care, the inconsistent availability of spirometry and symptom scores limits the detection of patients with poor disease control. There is a pr...

Robust comparative evaluation of 15 natural language processing algorithms to positively identify patients with inflammatory bowel disease from secondary care records.

BMJ open gastroenterology
OBJECTIVE: Natural language processing (NLP) can identify cohorts of patients with inflammatory bowel disease (IBD) from free text. However, limited sharing of code, models, and data sets continues to hinder progress. The aim of this study was to eva...

Design and implementation of a natural language processing system at the point of care: MiADE (medical information AI data extractor).

BMC medical informatics and decision making
BACKGROUND: Well-organised electronic health records (EHR) are essential for high quality patient care, but EHR user interfaces can be cumbersome for entry of structured information, resulting in the majority of information being in free text rather ...