AIMC Topic: Electronic Health Records

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Automate Creating, Customizing, and Optimizing Comorbidity Indices Using a Data-Driven AI/ML Approach.

Studies in health technology and informatics Aug 7, 2025
Due to individual differences in severity of illness, clinical studies typically use a comorbidity index to adjust outcomes. With the increasing use of electronic health records (EHRs) to assess the quality of care, a key question arises: how to adju...
Algorithms Humans Comorbidity Electronic Health Records Artificial Intelligence Hydroxymethylglutaryl-CoA Reductase Inhibitors
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AI Bias and Confounding Risk in Health Feature Engineering for Machine Learning Classification Task.

Studies in health technology and informatics Aug 7, 2025
Recent advancements in machine learning bring unique opportunities in health fields but also pose considerable challenges. Due to stringent ethical considerations and resource constraints, health data can vary in scope, population coverage, and colle...
Female Adult Electronic Health Records Pregnancy Bias Patient Readmission Confounding Factors, Epidemiologic Cardiovascular Diseases Risk Assessment Humans Machine Learning
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Leveraging Retrieval Augmented Generation-Driven Large Language Models to Extract Dementia Agitation Symptoms and Triggers from Free-Text Nursing Notes.

Studies in health technology and informatics Aug 7, 2025
Unstructured electronic health records are a rich source of patient-specific information but are challenging for analysis due to inconsistent terminology, diverse data formats, and extensive free-text content. To address this, we developed a named en...
Natural Language Processing Large Language Models Psychomotor Agitation Aberrant Motor Behavior in Dementia Electronic Health Records Nursing Records Humans Dementia Artificial Intelligence
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Beyond GPT-NER: ChatGPT as Ensemble Arbitrator for Discontinuous Named Entity Recognition in Health Corpora.

Studies in health technology and informatics Aug 7, 2025
In medicine and healthcare, NER (Named Entity Recognition) involves identifying clinically relevant entities such as medications, symptoms, and adverse drug events (ADEs). This task is particularly challenging due to discontinuous NER (DNER), fragmen...
Generative Artificial Intelligence Machine Learning Electronic Health Records Natural Language Processing Data Mining Humans
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The Best of All Worlds: A Hybrid Approach to Cohort Identification with Rules, Small and Large Language Models.

Studies in health technology and informatics Aug 7, 2025
Balancing operational feasibility with the performance of natural language processing (NLP) systems is a significant challenge. This study presents a hybrid strategy to integrate manually curated rules, small language model (SLM), and large language ...
Vocabulary, Controlled Large Language Models Natural Language Processing Data Mining Cohort Studies United States Humans Electronic Health Records
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Optimizing Entity Recognition in Psychiatric Treatment Data with Large Language Models.

Studies in health technology and informatics Aug 7, 2025
Extracting nuanced adverse drug reactions (ADRs) from patient self-reported messages using is pivotal but challenging, particularly given HIPAA constraints. We investigate locally deployable small LLMs-Mistral-7B, Llama-3-8B, and Gemma-7B-for ADR ext...
Drug-Related Side Effects and Adverse Reactions Data Mining Electronic Health Records Natural Language Processing Adverse Drug Reaction Reporting Systems Large Language Models Humans Mental Disorders
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Development and Evaluation of Natural Language Processing Methods for Extracting Key Melanoma Pathology Concepts.

Studies in health technology and informatics Aug 7, 2025
This study presents the development and evaluation of an annotation schema and rule-based natural language processing (NLP) system for extracting key melanoma pathology concepts from surgical pathology reports. Achieving high precision and recall, ou...
Humans Electronic Health Records Melanoma Data Mining Skin Neoplasms Natural Language Processing
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Comparative Analysis of NLP Models for Automatic LOINC Document Ontology Named Entity Recognition in Clinical Note Titles.

Studies in health technology and informatics Aug 7, 2025
In order to utilize clinical notes for research studies, it is necessary to identify the most relevant notes. Mapping to the LOINC Document Ontology makes this process easier by reducing the variability of note types. We experimented with three model...
Natural Language Processing Electronic Health Records Logical Observation Identifiers Names and Codes Pattern Recognition, Automated
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Multimodal Fusion of EHR in Structures and Semantics: Integrating Clinical Records and Notes with Hypergraph and LLM.

Studies in health technology and informatics Aug 7, 2025
In recent decades, Electronic Health Records (EHRs) have become increasingly useful to support clinical decision-making and healthcare. EHRs usually contain heterogeneous information, such as structural data in tabular form and un-structured data in ...
Semantics Humans Neural Networks, Computer Electronic Health Records Natural Language Processing
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Improving Zero-Shot Multiclass Classification for Narrative Reports from National Violent Death Reporting System.

Studies in health technology and informatics Aug 7, 2025
The natural language processing pipeline powered by the BART model is a popular zero-shot text classification system. While the standard approach for using this pipeline can achieve impressive accuracies in many multiclass classification tasks, we be...
Humans Narration Natural Language Processing Violence Electronic Health Records United States
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