AIMC Topic: Information Storage and Retrieval

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Entity replacement strategy for temporal knowledge graph query relaxation.

Neural networks : the official journal of the International Neural Network Society
The temporal knowledge graph (TKG) query enables the retrieval of candidate answer lists by addressing questions that involve temporal constraints, regarded as a crucial downstream task in the realm of the temporal knowledge graph. Existing methods p...

LitSense 2.0: AI-powered biomedical information retrieval with sentence and passage level knowledge discovery.

Nucleic acids research
LitSense 2.0 (https://www.ncbi.nlm.nih.gov/research/litsense2/) is an advanced biomedical search system enhanced with dense vector semantic retrieval, designed for accessing literature on sentence and paragraph levels. It provides unified access to 3...

Dynamic few-shot prompting for clinical note section classification using lightweight, open-source large language models.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Unlocking clinical information embedded in clinical notes has been hindered to a significant degree by domain-specific and context-sensitive language. Identification of note sections and structural document elements has been shown to impro...

Enhancing search strategies for systematic reviews on drug Harms: An evaluation of the utility of ChatGPT in error detection and keyword generation.

Computers in biology and medicine
OBJECTIVE: Developing search strategies for synthesizing evidence on drug harms requires specialized expertise and knowledge. The aim of this study was to evaluate ChatGPT's ability to enhance search strategies for systematic reviews of drug harms by...

A comparative analysis of privacy-preserving large language models for automated echocardiography report analysis.

Journal of the American Medical Informatics Association : JAMIA
BACKGROUND: Automated data extraction from echocardiography reports could facilitate large-scale registry creation and clinical surveillance of valvular heart diseases (VHD). We evaluated the performance of open-source large language models (LLMs) gu...

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...

DNA-CBIR: DNA Translation Inspired Codon Pattern-Based Deep Image Feature Extraction for Content-Based Image Retrieval.

IEEE transactions on nanobioscience
DNA is emerging as a promising medium for storing huge volumes of data in a confined space that remains intact for thousands of years. Although this technique is very efficient, especially for multimedia data like images, there is a lack of efficient...

LITERAS: Biomedical literature review and citation retrieval agents.

Computers in biology and medicine
BACKGROUND: Existing tools for reference retrieval using large language models (LLMs) frequently generate inaccurate, gray literature or fabricated citations, leading to poor accuracy. In this study, we aim to address this gap by developing a highly ...

The Role of Artificial Intelligence Large Language Models in Literature Search Assistance to Evaluate Inguinal Hernia Repair Approaches.

Journal of laparoendoscopic & advanced surgical techniques. Part A
This study assesses the reliability of artificial intelligence (AI) large language models (LLMs) in identifying relevant literature comparing inguinal hernia repair techniques. We used LLM chatbots (Bing Chat AI, ChatGPT versions 3.5 and 4.0, and G...

Recovering missing electronic health record mortality data with a machine learning-enhanced data linkage process.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: To develop a continual process for linking more comprehensive external mortality data to electronic health records (EHRs) for a large healthcare system, which can serve as a template for other healthcare systems.