Tag:
Computational biology and bioinformatics
AI
An Empowered AI Framework for the Ingestion and Standardization of Single-Cell RNA-Seq Data Analysis
CellAtria is an advanced agentic system designed to streamline single-cell research by automating data extraction, metadata retrieval, and analysis workflows. Its architectural framework supports...
AI
PromptGuard: A Robust Framework for Enhancing Injection Resilience in Language Models
Title: Effective Defense Against Prompt Injection in LLMs
The methodology outlined in this study details a structured, modular workflow for defending against prompt injection in...
AI
Revolutionizing Diagnostic and Therapeutic Approaches in Chronic Liver Disease: The Role of AI-Based Agents in Clinical Decision-Making
Chronic liver diseases include a spectrum of conditions such as metabolic dysfunction-associated steatotic liver disease (MASLD), steatohepatitis (MASH), alcohol-related liver disease (ALD), metabolic-ALD (met-ALD),...
AI
Transforming Biomedicine and Healthcare with Large Language Models
The survey of large language models (LLMs) reveals their expanding role across various domains, notably healthcare. Zhao et al. (2023) explore the capabilities of...
AI
Leveraging Large Language Models to Predict Patient Health Trajectories for Enhanced Digital Twin Applications
DT-GPT is a novel framework that utilizes fine-tuned pre-trained large language models (LLMs) on clinical data to forecast patients' laboratory values. This method is...
AI
MAIA: An AI-Powered Embryo Selection Tool for Enhancing Routine Clinical Testing in Embryology
The advancement of Assisted Reproductive Technology (ART) and artificial intelligence (AI) has revolutionized infertility treatment. Key studies, including Graham et al. (2023) and Jiang...
AI
Transforming Healthcare: Integrating Education, Research, AI, and Personalized Learning for Inclusivity
The Stanford Data Ocean (SDO) focuses on three key areas: robust data management for diverse multi-omics and wearable datasets, personalized education leveraging large-scale datasets,...
AI
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...