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

Showing 121 to 130 of 493 articles

TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Our objective is to develop and validate TrajVis, an interactive tool that assists clinicians in using artificial intelligence (AI) models to leverage patients' longitudinal electronic medical records (EMRs) for personalized precision mana...

A question-answering framework for automated abstract screening using large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: This paper aims to address the challenges in abstract screening within systematic reviews (SR) by leveraging the zero-shot capabilities of large language models (LLMs).

Reasoning with large language models for medical question answering.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To investigate approaches of reasoning with large language models (LLMs) and to propose a new prompting approach, ensemble reasoning, to improve medical question answering performance with refined reasoning and reduced inconsistency.

The first step is the hardest: pitfalls of representing and tokenizing temporal data for large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: Large language models (LLMs) have demonstrated remarkable generalization and across diverse tasks, leading individuals to increasingly use them as personal assistants due to their emerging reasoning capabilities. Nevertheless, a notable o...

Disambiguation of acronyms in clinical narratives with large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To assess the performance of large language models (LLMs) for zero-shot disambiguation of acronyms in clinical narratives.

LEAP: LLM instruction-example adaptive prompting framework for biomedical relation extraction.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To investigate the demonstration in large language models (LLMs) for biomedical relation extraction. This study introduces a framework comprising three types of adaptive tuning methods to assess their impacts and effectiveness.

A publishing infrastructure for Artificial Intelligence (AI)-assisted academic authoring.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Investigate the use of advanced natural language processing models to streamline the time-consuming process of writing and revising scholarly manuscripts.

BioInstruct: instruction tuning of large language models for biomedical natural language processing.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To enhance the performance of large language models (LLMs) in biomedical natural language processing (BioNLP) by introducing a domain-specific instruction dataset and examining its impact when combined with multi-task learning principles.

Fine-tuning large language models for rare disease concept normalization.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We aim to develop a novel method for rare disease concept normalization by fine-tuning Llama 2, an open-source large language model (LLM), using a domain-specific corpus sourced from the Human Phenotype Ontology (HPO).

Knowledge-guided generative artificial intelligence for automated taxonomy learning from drug labels.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVES: To automatically construct a drug indication taxonomy from drug labels using generative Artificial Intelligence (AI) represented by the Large Language Model (LLM) GPT-4 and real-world evidence (RWE).