AI Medical Compendium Journal:
Journal of the American Medical Informatics Association : JAMIA

Showing 81 to 90 of 493 articles

A novel generative multi-task representation learning approach for predicting postoperative complications in cardiac surgery patients.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Early detection of surgical complications allows for timely therapy and proactive risk mitigation. Machine learning (ML) can be leveraged to identify and predict patient risks for postoperative complications. We developed and validated the...

Analysis of eligibility criteria clusters based on large language models for clinical trial design.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Clinical trials (CTs) are essential for improving patient care by evaluating new treatments' safety and efficacy. A key component in CT protocols is the study population defined by the eligibility criteria. This study aims to evaluate the...

Enhancing patient representation learning with inferred family pedigrees improves disease risk prediction.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Machine learning and deep learning are powerful tools for analyzing electronic health records (EHRs) in healthcare research. Although family health history has been recognized as a major predictor for a wide spectrum of diseases, research...

CARE-SD: classifier-based analysis for recognizing provider stigmatizing and doubt marker labels in electronic health records: model development and validation.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To detect and classify features of stigmatizing and biased language in intensive care electronic health records (EHRs) using natural language processing techniques.

Application of large language models in clinical record correction: a comprehensive study on various retraining methods.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: We evaluate the effectiveness of large language models (LLMs), specifically GPT-based (GPT-3.5 and GPT-4) and Llama-2 models (13B and 7B architectures), in autonomously assessing clinical records (CRs) to enhance medical education and dia...

Lessons learned on information retrieval in electronic health records: a comparison of embedding models and pooling strategies.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Applying large language models (LLMs) to the clinical domain is challenging due to the context-heavy nature of processing medical records. Retrieval-augmented generation (RAG) offers a solution by facilitating reasoning over large text so...

Ambient artificial intelligence scribes: utilization and impact on documentation time.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To quantify utilization and impact on documentation time of a large language model-powered ambient artificial intelligence (AI) scribe.

Beyond electronic health record data: leveraging natural language processing and machine learning to uncover cognitive insights from patient-nurse verbal communications.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Mild cognitive impairment and early-stage dementia significantly impact healthcare utilization and costs, yet more than half of affected patients remain underdiagnosed. This study leverages audio-recorded patient-nurse verbal communicatio...

Toward an artificial intelligence code of conduct for health and healthcare: implications for the biomedical informatics community.

Journal of the American Medical Informatics Association : JAMIA
INTRODUCTION: The rapid advancement of artificial intelligence (AI) has led to significant transformations in health and healthcare. As AI technologies continue to evolve, there is an urgent need to establish a unified framework that guides the desig...

Regulation of artificial intelligence in healthcare: Clinical Laboratory Improvement Amendments (CLIA) as a model.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To assess the potential to adapt an existing technology regulatory model, namely the Clinical Laboratory Improvement Amendments (CLIA), for clinical artificial intelligence (AI).