AIMC Topic: Electronic Health Records
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Development of a Mapping Table for Nursing Notes Based on Nurses' Concerns in ICU Patients.
Studies in health technology and informatics
Jul 24, 2024
This study aimed to develop a mapping table that connects nursing notes with standard terminology, focusing on nurses' concerns for ICU patients. After extracting nursing notes from a publicly accessible database, a research team, including a nursing...
Development of a Nursing Diagnosis/Record Generative AI System Based on Virtual Patient Data.
Studies in health technology and informatics
Jul 24, 2024
This study investigates how to reduce nurses' repetitive electronic nursing record tasks. We applied generative AI by learning nursing record data practiced with virtual patient data. We aim to evaluate generative AI's usefulness, usability, and avai...
Machine Learning-Based Prediction Models of Mortality for Intensive Care Unit Patients Using Nursing Records.
Studies in health technology and informatics
Jul 24, 2024
This study aimed to develop ICU mortality prediction models using a conceptual framework, focusing on nurses' concerns reflected in nursing records from the MIMIC IV database. We included 46,693 first-time ICU admissions of adults over 18 years with ...
Deep Learning for Predicting Phlebitis in Patients with Intravenous Catheters.
Studies in health technology and informatics
Jul 24, 2024
This study presents a deep learning model to predict phlebitis in patients with peripheral intravenous catheter (PIVC) insertions. Leveraging electronic health record data from 27,532 admissions and 70,293 PIVC events at a hospital in Seoul, South Ko...
Unveiling Fall Risk Factors: Nurse-Driven Corpus Development for Natural Language Processing.
Studies in health technology and informatics
Jul 24, 2024
Hospital-acquired falls are a continuing clinical concern. The emergence of advanced analytical methods, including NLP, has created opportunities to leverage nurse-generated data, such as clinical notes, to better address the problem of falls. In thi...
Fairness in Classifying and Grouping Health Equity Information.
Studies in health technology and informatics
Jul 24, 2024
This paper explores the balance between fairness and performance in machine learning classification, predicting the likelihood of a patient receiving anti-microbial treatment using structured data in community nursing wound care electronic health rec...
Machine Learning in Electronic Health Records: Identifying High-Risk Obstetric Patients Pre and During Labor.
Studies in health technology and informatics
Jul 24, 2024
Our goal is to apply artificial intelligence (AI) and statistical analysis to understand the relationship between various factors and outcomes during pregnancy and labor and delivery, in order to personalize birth management and reduce complications ...
The use of natural language processing for the identification of ageing syndromes including sarcopenia, frailty and falls in electronic healthcare records: a systematic review.
Age and ageing
Jul 2, 2024
BACKGROUND: Recording and coding of ageing syndromes in hospital records is known to be suboptimal. Natural Language Processing algorithms may be useful to identify diagnoses in electronic healthcare records to improve the recording and coding of the...
Cost-Saving Data-Driven Diabetic Retinopathy Prediction via a Sampling-Empowered Incremental Learning Approach.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Diabetic retinopathy (DR) is a serious complication of diabetes that can lead to vision impairment or even blindness if not detected and treated in the early stage. Recently, leveraging the electronic health records (EHR) data, machine learning-based...
High Throughput Phenotyping of Physician Notes with Large Language and Hybrid NLP Models.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
Deep phenotyping is the detailed description of patient signs and symptoms using concepts from an ontology. The deep phenotyping of the numerous physician notes in electronic health records requires high throughput methods. Over the past 30 years, pr...
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