AIMC Topic: Information Storage and Retrieval
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Evaluating a Customized Version of ChatGPT for Systematic Review Data Extraction in Health Research: Development and Usability Study.
JMIR formative research
Aug 11, 2025
BACKGROUND: Systematic reviews are essential for synthesizing research in health sciences; however, they are resource-intensive and prone to human error. The data extraction phase, in which key details of studies are identified and recorded in a syst...
Autoencoder-Based Representation Learning for Similar Patients Retrieval From Electronic Health Records: Comparative Study.
JMIR medical informatics
Jul 24, 2025
BACKGROUND: By analyzing electronic health record snapshots of similar patients, physicians can proactively predict disease onsets, customize treatment plans, and anticipate patient-specific trajectories. However, the modeling of electronic health re...
Random access and semantic search in DNA data storage enabled by Cas9 and machine-guided design.
Nature communications
Jul 10, 2025
DNA is a promising medium for digital data storage due to its exceptional data density and longevity. Practical DNA-based storage systems require selective data retrieval to minimize decoding time and costs. In this work, we introduce CRISPR-Cas9 as ...
Optimizing visual data retrieval using deep learning driven CBIR for improved human machine interaction.
Scientific reports
Jul 2, 2025
Content-based image retrieval (CBIR) systems have formidable obstacles in connecting human comprehension with machine-driven feature extraction due to the exponential expansion of visual data across many areas. Robust performance across varied datase...
Particle swarm optimization-based NLP methods for optimizing automatic document classification and retrieval.
PloS one
Jul 2, 2025
Text classification plays an essential role in natural language processing and is commonly used in tasks like categorizing news, sentiment analysis, and retrieving relevant information. [0pc][-9pc]Please check and confirm the inserted city and countr...
Evaluating large language models for information extraction from gastroscopy and colonoscopy reports through multi-strategy prompting.
Journal of biomedical informatics
Jun 10, 2025
OBJECTIVE: To systematically evaluate large language models (LLMs) for automated information extraction from gastroscopy and colonoscopy reports through prompt engineering, addressing their ability to extract structured information, recognize complex...
Streamlining systematic reviews with large language models using prompt engineering and retrieval augmented generation.
BMC medical research methodology
May 10, 2025
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
Apr 30, 2025
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...
Using Large Language Models to Automate Data Extraction From Surgical Pathology Reports: Retrospective Cohort Study.
JMIR formative research
Apr 7, 2025
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...
Using artificial intelligence tools to automate data extraction for living evidence syntheses.
PloS one
Apr 3, 2025
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...
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