Knowledge Management in Medicine with AI: From Medical Databases to Decision Support at the Point of Care

In the digital age, knowledge management in medicine has become a fundamental pillar for effective clinical practice. The integration of artificial intelligence (AI) in medical databases offers an unprecedented opportunity to transform how physicians access and utilize information at the point of care. This article explores how AI is revolutionizing decision support in clinical settings, enabling continuous updating of medical knowledge and facilitating the work of the connected doctor.
AI in Medical Knowledge Management
The implementation of AI-based clinical decision support systems (AI-CDSS) in primary care has proven to be promising. These systems not only assist in diagnosis and treatment but also reduce the workload of physicians and healthcare costs. However, their effectiveness may be influenced by cultural perceptions and acceptance among doctors.
Moreover, data mining and natural language processing are enhancing the quality of medical reports, such as those in radiology, by quantifying and analyzing uncertainty in reports. This not only improves diagnostic accuracy but also optimizes real-time clinical decision-making.
On the other hand, the use of ontologies to structure organizational knowledge in home care has proven effective. Ontologies allow for an unambiguous representation of medical terminology and facilitate adaptation to changes in healthcare organization, improving efficiency and personalization of services.
Conclusions
The integration of AI in medical knowledge management from medical databases to the point of care is transforming clinical practice. Decision support systems, data mining, and ontologies are powerful tools that enable physicians to stay updated and make informed decisions more efficiently. As these technologies continue to evolve, it is crucial for healthcare professionals to adapt and embrace these innovations to enhance the quality of patient care.
Referencias
- [1] Artificial-Intelligence-Based Clinical Decision Support Systems in Primary Care: A Scoping Review of Current Clinical Implementations
- [2] Uncovering and improving upon the inherent deficiencies of radiology reporting through data mining
- [3] Using ontologies for structuring organizational knowledge in Home Care assistance
Created 20/1/2025