AI Medical Compendium Topic:
Electronic Health Records

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Facilitating the Development of Deep Learning Models with Visual Analytics for Electronic Health Records.

International journal of environmental research and public health
Electronic health record (EHR) data are widely used to perform early diagnoses and create treatment plans, which are key areas of research. We aimed to increase the efficiency of iteratively applying data-intensive technology and verifying the result...

Machine Learning to Predict Mortality and Critical Events in a Cohort of Patients With COVID-19 in New York City: Model Development and Validation.

Journal of medical Internet research
BACKGROUND: COVID-19 has infected millions of people worldwide and is responsible for several hundred thousand fatalities. The COVID-19 pandemic has necessitated thoughtful resource allocation and early identification of high-risk patients. However, ...

Artificial Intelligence in the Intensive Care Unit.

Seminars in respiratory and critical care medicine
The diffusion of electronic health records collecting large amount of clinical, monitoring, and laboratory data produced by intensive care units (ICUs) is the natural terrain for the application of artificial intelligence (AI). AI has a broad definit...

TAPER: Time-Aware Patient EHR Representation.

IEEE journal of biomedical and health informatics
Effective representation learning of electronic health records is a challenging task and is becoming more important as the availability of such data is becoming pervasive. The data contained in these records are irregular and contain multiple modalit...

Predicting preventable hospital readmissions with causal machine learning.

Health services research
OBJECTIVE: To assess both the feasibility and potential impact of predicting preventable hospital readmissions using causal machine learning applied to data from the implementation of a readmissions prevention intervention (the Transitions Program).

Combining structured and unstructured data for predictive models: a deep learning approach.

BMC medical informatics and decision making
BACKGROUND: The broad adoption of electronic health records (EHRs) provides great opportunities to conduct health care research and solve various clinical problems in medicine. With recent advances and success, methods based on machine learning and d...

Prediction of severe chest injury using natural language processing from the electronic health record.

Injury
INTRODUCTION: Trauma injury severity scores are currently calculated retrospectively from the electronic health record (EHR) using manual annotation by certified trauma coders. Natural language processing (NLP) of clinical documents in the EHR may en...

Cross domains adversarial learning for Chinese named entity recognition for online medical consultation.

Journal of biomedical informatics
Deep learning methods have been applied to Chinese named entity recognition for the online medical consultation. They require a large number of marked samples. However, no such database is available at present. This paper begins with constructing a l...

Prediction of obstetrical and fetal complications using automated electronic health record data.

American journal of obstetrics and gynecology
An increasing number of delivering women experience major morbidity and mortality. Limited work has been done on automated predictive models that could be used for prevention. Using only routinely collected obstetrical data, this study aimed to devel...