AI in Clinical Guideline Updates: Rapid Access to Evidence through Recommendation Algorithms and Medical Libraries

The updating of clinical guidelines is an essential process to ensure that healthcare professionals have access to the best practices based on the most recent evidence. In this context, artificial intelligence (AI) is emerging as a powerful tool to facilitate rapid access to evidence and personalize clinical recommendations. The integration of AI into medical libraries and recommendation algorithms is transforming how physicians access and apply information in their daily practice.
AI in the Personalization of Clinical Guidelines
AI is revolutionizing the way clinical guidelines are updated and distributed. Platforms like OpenClinical.net combine the power of AI with human knowledge to provide specific recommendations for each patient. This approach not only enhances the quality of care but also allows healthcare professionals to create, share, and review best practice models more efficiently.
Moreover, AI is being used to automate the analysis of scientific literature, as seen in the system developed for clinical oncology, which enables timely access to the most relevant biomedical literature. Such tools are crucial in areas of medicine where science evolves rapidly, providing critical support for evidence-based practice.
However, the implementation of AI in clinical practice is not without challenges. The perception of healthcare professionals regarding AI reveals concerns about data privacy, professional autonomy, and algorithmic bias. It is essential to address these issues to ensure that AI is used ethically and effectively.
Conclusions
The integration of AI in the updating of clinical guidelines offers significant potential to improve the efficiency and accuracy of clinical decisions. By providing rapid and personalized access to evidence, AI can help physicians stay up-to-date with scientific advancements and apply best practices in patient care. Nevertheless, it is crucial for AI developers to collaborate with healthcare professionals to address ethical and practical challenges, ensuring that these technologies are used responsibly and effectively.
Referencias
- [1] OpenClinical.net: Artificial intelligence and knowledge engineering at the point of care
- [2] Artificial Intelligence Clinical Evidence Engine for Automatic Identification, Prioritization, and Extraction of Relevant Clinical Oncology Research
- [3] Multi-stakeholder preferences for the use of artificial intelligence in healthcare: A systematic review and thematic analysis
Created 20/1/2025