Saturday, August 16, 2025
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Revealing the Surprising Power of Large Language Models in Predicting Aging Status

In a groundbreaking study published in Nature Medicine, Li et al. explore the use of large language models (LLMs) for predicting biological age across...

A Practical Guide to Implementing and Reviewing Artificial Intelligence in Healthcare (FAIR-AI)

The narrative review outlines best practices for responsibly deploying AI in healthcare as part of the FAIR-AI framework, focusing on validation, transparency, equity, and...

Comprehensive Assurance Analysis Reveals High Vulnerability of Large Language Models to Adversarial Hallucination Attacks in Clinical Decision Support

In this study, we examined multiple Large Language Models (LLMs) under adversarial hallucination attacks in clinical contexts by embedding fabricated content. We varied text...

Transforming Ophthalmology: How a Large Language Model Digital Patient System Improves History-Taking Skills

This study focuses on constructing an ophthalmic dataset and evaluating various large language models (LLMs) to enhance medical education through a digital patient simulation...

Assessing the Utilization of Large Language Models in Scientific Research Publications

Recent discussions highlight the increasing use of AI tools like ChatGPT in academic research, raising concerns about academic integrity and the reliability of scientific...

Integrating Large Language Models in Cancer Decision-Making: A Comprehensive Systematic Review and Meta-Analysis

In our systematic review, we analyzed 56 studies focusing on AI-based chatbots and their role in clinical decision support for cancer patients. Following rigorous...

Empowering Gene Editing: CRISPR-GPT for Automated Experimental Precision

CRISPR-GPT is an advanced AI co-pilot leveraging large language models (LLMs) to streamline gene-editing workflows, supporting four major modalities across 22 specific tasks. It...

Evaluating Large Language Models for the Replication of Guideline-Based Pharmacogenomic Recommendations

The understanding of adverse drug reactions (ADRs) is critical in clinical medicine, as highlighted by Coleman and Pontefract (2016), emphasizing the need for vigilance...