LLMs-Healthcare : Current Applications and Challenges of Large Language Models in various Medical Specialties

📰 ArXiv cs.AI

Large Language Models (LLMs) are transforming healthcare across various medical specialties, but also pose challenges

intermediate Published 7 Apr 2026
Action Steps
  1. Identify areas where LLMs can augment clinical decision-making, such as diagnosis and treatment planning
  2. Assess the potential of LLMs to improve patient engagement and personalized medicine
  3. Evaluate the challenges of integrating LLMs into existing healthcare systems, including data quality and regulatory compliance
  4. Develop strategies to address these challenges and ensure effective deployment of LLMs in healthcare
Who Needs to Know This

Data scientists, AI engineers, and healthcare professionals can benefit from understanding LLM applications in healthcare to improve patient outcomes and streamline clinical workflows

Key Insight

💡 LLMs have the potential to transform healthcare, but their adoption requires careful consideration of challenges and limitations

Share This
💡 LLMs are revolutionizing healthcare! From diagnosis to patient engagement, the possibilities are vast #LLMs #Healthcare
Read full paper → ← Back to Reads