Keywords
healthcare
machine learning
anonymization
MongoDB
security
How to Cite
Abstract
The paper highlights the crucial role of databases in the process of integrating machine learning algorithms in the healthcare sector, especially on the example of a symptom-based presumptive diagnosis system. As the foundation of the digital transformation of healthcare, databases provide flexible data collection, reliable storage, efficient processing, and secure anonymization, which allows machine learning models to generate accurate and personalized medical recommendations. The example of MongoDB shows how the flexibility of a NoSQL database helps manage complex clinical data structures, while security mechanisms such as encryption and access control protect patient confidentiality.
The paper presents a detailed description of the data model, implementation of security mechanisms, and practical examples that clearly demonstrate how effective database management contributes to the digital transformation of the healthcare sector. The study emphasizes that effective database management is not only a technical necessity, but also an ethical and legal obligation in terms of protecting sensitive data in the healthcare sector.
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