AIMC Topic: Electronic Health Records

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Federated Multiple Imputation for Variables that Are Missing Not At Random in Distributed Electronic Health Records.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Large electronic health records (EHR) have been widely implemented and are available for research activities. The magnitude of such databases often requires storage and computing infrastructure that are distributed at different sites. Restrictions on...

Early Disease Prediction Using a Text-Numerical Hybrid Model Using Large-Scale Clinical Real-World Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
To assist physicians in predicting diseases, most natural language processing (NLP) models have focused on progress notes in electronic medical records with full descriptions from the initial stage of patient diagnosis to the final stage of discharge...

An Interpretable Population Graph Network to Identify Rapid Progression of Alzheimer's Disease Using UK Biobank.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Alzheimer's disease (AD) manifests with varying progression rates across individuals, necessitating the understanding of their intricate patterns of cognition decline that could contribute to effective strategies for risk monitoring. In this study, w...

Enhancing Patient Medication Safety at Home: A Patient-Facing Technology Architecture Integrating REDCap, Visualization Dashboards, and an AI- Driven Chatbot.

AMIA ... Annual Symposium proceedings. AMIA Symposium
This work demonstrates a novel architecture for a patient-facing technology (PFT) that supports patients with cancer in self-managing medication concerns and symptoms after care transitions back home. Patient-generated data are collected and stored u...

A Generative Foundation Model for Structured Patient Trajectory Data.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Advancements in artificial intelligence propelled the implementation of general-purpose multitasking agents called foundation models. However, it has been challenging for foundation models to handle structured longitudinal medical data due to the mix...

Neural Granger Causal Discovery for Derangements in ICU-Acquired Acute Kidney Injury Patients.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Nowadays, healthcare systems increasingly utilize automated surveillance of electronic medical record (EMR) data to detect adverse events with specific patterns. Despite these technological advances, the early identification of adverse events remains...

LLMs-based Few-Shot Disease Predictions using EHR: A Novel Approach Combining Predictive Agent Reasoning and Critical Agent Instruction.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Electronic health records (EHRs) contain valuable patient data for health-related prediction tasks, such as disease prediction. Traditional approaches rely on supervised learning methods that require large labeled datasets, which can be expensive and...

Boosting Social Determinants of Health Extraction with Semantic Knowledge Augmented Large Language Model.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Social determinants of health (SDoH) significantly impacts health outcomes and contributes to perpetuating health disparities across healthcare applications. However, automatic extraction of SDoH information from Electronic Health Records (EHRs) is c...

Extraction of Normalized Symptom Mentions From Clinical Narratives Using Large Language Models.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Symptoms, or subjective experiences of patients which can indicate underlying pathology, are important for guiding clinician decision-making and revealing patient wellbeing. However, they are difficult to study because information is primarily found ...