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To evaluate the capability of using generative artificial intelligence (AI) in summarizing alert comments and to determine if the AI-generated summary could be used to improve clinical decision support (CDS) alerts.

This study evaluates an AI assistant developed using OpenAI's GPT-4 for interpreting pharmacogenomic (PGx) testing results, aiming to improve decision-making and knowledge sharing in clinical genetics and to enhance patient care with equitable access.

This article explores the potential of large language models (LLMs) to automate administrative tasks in healthcare, alleviating the burden on clinicians caused by electronic medical records.

Large-language models (LLMs) can potentially revolutionize health care delivery and research, but risk propagating existing biases or introducing new ones. In epilepsy, social determinants of health are associated with disparities in care access, but their impact on seizure outcomes among those with access remains unclear. Here we (1) evaluated our validated, epilepsy-specific LLM for intrinsic bias, and (2) used LLM-extracted seizure outcomes to determine if different demographic groups have different [...]

This study aimed to support the implementation of the 11th Revision of the International Classification of Diseases (ICD-11). We used common comorbidity indices as a case study for proactively assessing the impact of transitioning to ICD-11 for mortality and morbidity statistics (ICD-11-MMS) on real-world data analyses.

This study aimed to develop and assess the performance of fine-tuned large language models for generating responses to patient messages sent via an electronic health record patient portal.

Genomic kidney conditions often have a long lag between onset of symptoms and diagnosis. To design a real time genetic diagnosis process that meets the needs of nephrologists, we need to understand the current state, barriers, and facilitators nephrologists and other clinicians who treat kidney conditions experience, and identify areas of opportunity for improvement and innovation.

To investigate the consistency and reliability of medication recommendations provided by ChatGPT for common dermatological conditions, highlighting the potential for ChatGPT to offer second opinions in patient treatment while also delineating possible limitations.

To compare performances of a classifier that leverages language models when trained on synthetic versus authentic clinical notes.