AI Medical Compendium Topic

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Information Storage and Retrieval

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Streamlining systematic reviews with large language models using prompt engineering and retrieval augmented generation.

BMC medical research methodology
BACKGROUND: Systematic reviews (SRs) are essential to formulate evidence-based guidelines but require time-consuming and costly literature screening. Large Language Models (LLMs) can be a powerful tool to expedite SRs.

Use of Retrieval-Augmented Large Language Model for COVID-19 Fact-Checking: Development and Usability Study.

Journal of medical Internet research
BACKGROUND: The COVID-19 pandemic has been accompanied by an "infodemic," where the rapid spread of misinformation has exacerbated public health challenges. Traditional fact-checking methods, though effective, are time-consuming and resource-intensiv...

Retrieval Augmented Generation: What Works and Lessons Learned.

Studies in health technology and informatics
Retrieval Augmented Generation has been shown to improve the output of large language models (LLMs) by providing context to the question or scenario posed to the model. We have tried a series of experiments to understand how best to improve the perfo...

Using artificial intelligence tools to automate data extraction for living evidence syntheses.

PloS one
Living evidence synthesis (LES) involves repeatedly updating a systematic review or meta-analysis at regular intervals to incorporate new evidence into the summary results. It requires a considerable amount of human time investment in the article sea...

Unambiguous granularity distillation for asymmetric image retrieval.

Neural networks : the official journal of the International Neural Network Society
Previous asymmetric image retrieval methods based on knowledge distillation have primarily focused on aligning the global features of two networks to transfer global semantic information from the gallery network to the query network. However, these m...

Revisiting medical image retrieval via knowledge consolidation.

Medical image analysis
As artificial intelligence and digital medicine increasingly permeate healthcare systems, robust governance frameworks are essential to ensure ethical, secure, and effective implementation. In this context, medical image retrieval becomes a critical ...

Integrating PICO principles into generative artificial intelligence prompt engineering to enhance information retrieval for medical librarians.

Journal of the Medical Library Association : JMLA
Prompt engineering, an emergent discipline at the intersection of Generative Artificial Intelligence (GAI), library science, and user experience design, presents an opportunity to enhance the quality and precision of information retrieval. An innovat...

Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study.

JMIR formative research
BACKGROUND: Popularized by ChatGPT, large language models (LLMs) are poised to transform the scalability of clinical natural language processing (NLP) downstream tasks such as medical question answering (MQA) and automated data extraction from clinic...

Careful design of Large Language Model pipelines enables expert-level retrieval of evidence-based information from syntheses and databases.

PloS one
Wise use of evidence to support efficient conservation action is key to tackling biodiversity loss with limited time and resources. Evidence syntheses provide key recommendations for conservation decision-makers by assessing and summarising evidence,...

A comparative analysis of large language models versus traditional information extraction methods for real-world evidence of patient symptomatology in acute and post-acute sequelae of SARS-CoV-2.

PloS one
BACKGROUND: Patient symptoms, crucial for disease progression and diagnosis, are often captured in unstructured clinical notes. Large language models (LLMs) offer potential advantages in extracting patient symptoms compared to traditional rule-based ...