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Information Technology

Latest AI and machine learning research in information technology for healthcare professionals.

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Development of the Short Hospitalization Predictor (SHoP) Machine Learning Model Across Two Hospitals

To develop and evaluate an open-source machine learning (ML) models for predicting hospital short st...

Leveraging neighborhood-level Information to Improve Model Fairness in Predicting Prenatal Depression

Perinatal depression (PND) affects 10-20% of pregnant women, with significant racial disparities in ...

Testing and Evaluation of Generative Large Language Models in Electronic Health Record Applications: A Systematic Review

The use of generative large language models (LLMs) with electronic health record (EHR) data is rapid...

Predicting the need for electroconvulsive therapy via machine learning trained on electronic health record data

Electroconvulsive therapy (ECT) is an effective treatment of severe manifestations of mental illness...

Interoperability of standardised electronic healthcare records facilitates transfer learning

Electronic healthcare records (EHR) use codes from different vocabularies to describe medical occurr...

Artificial Intelligence for Early Detection and Prognosis Prediction of Diabetic Retinopathy

This review explores the transformative role of artificial intelligence (AI) in the early detection ...

A machine learning approach for automating review of a RxNorm medication mapping pipeline output

Medication mapping to standardized terminologies is an important prerequisite for performing analyti...

Domain Adaptation Strategies for Transformer-Based Disease Prediction Using Electronic Health Records

Electronic Health Records (EHRs) offer rich data for machine learning, but model generalizability ac...

Semantic Encoding in Medical LLMs for Vocabulary Standardisation

High-quality, standardised medical data availability remains a bot-tleneck for digital health and AI...

Gaps in Artificial Intelligence Research for Rural Health in the United States: A Scoping Review

Artificial intelligence (AI) has impacted healthcare at urban and academic medical centers globally....

Bridging the Heterogeneity of Myasthenia Gravis Severity Scores for Digital Twin Development

Myasthenia gravis (MG) is a rare autoimmune neuromuscular disease. Clinical trials with rigorously c...

Early Warning Model for Patient Deterioration: A Machine Learning Approach for Nurse-Led Monitoring

The early recognition of clinical deterioration in hospital inpatients continues to be a major chall...

Artificial Intelligence Enabled Phenogrouping of Heart Failure with Preserved Ejection Fraction Depicts Early and End-Stage Trajectories

Heart failure with preserved ejection fraction is challenging to diagnose, precluding the initiation...

Automated Insomnia Phenotyping from Electronic Health Records: Leveraging Large Language Models to Decode Clinical Narratives

Insomnia is a highly prevalent but often underdiagnosed condition in clinical practice. Its inconsis...

Enhancing Cause of Death Prediction: Development and Validation of ML Models Using Multimodal Data Across Multiple Healthcare Sites

Timely and accurate determination of causes of death (CoD) is essential for public health surveillan...

Design and Implementation of an End-to-End AI-Driven Colonoscopy Recall Workflow at Scale

We present a real-world deployment of a large language model-powered colonoscopy recall pipeline tha...

Automatic ICD coding using LLMs: a systematic review

Manual assignment of International Classification of Diseases (ICD) codes is error-prone. Transforme...

Zero-Shot Large Language Models for Long Clinical Text Summarization with Temporal Reasoning

Recent advances in large language models (LLMs) have shown potential in clinical text summarization,...

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