Technological Strategies for Efficient Medical Data Retrieval in Interconnected Healthcare Systems: A Review

Nowadays, the management of digital medical images faces increasing challenges due to the volume, diversity, and need for interoperability between systems. The DICOM standard has become the main format for storing and transmitting medical images, enabling the integration of data from studies such as MRI, CT, and USG. However, its complex structure and the increasing volume of data generated by interconnected devices, including IoT sensors, demand new strategies for efficient storage and retrieval. Clinical databases must support large volumes of heterogeneous data while ensuring fast access, availability, and secure information exchange. This review explores the integration of the DICOM standard with medical database systems, emphasizing the role of sensors as a primary source in clinical data management. The findings aim to support the development of more effective strategies for data retrieval and exchange, such as database fragmentation, to reduce query response times and improve information systems used by healthcare professionals and patients. Additionally, various data sets or benchmarks used in the analyzed studies are described. As a result, two approaches are identified as particularly noteworthy among the reviewed works, serving as a reference for future applications and technological developments in healthcare.