Optimizing an AI-Based Diagnostic System for Infectious Diseases through Medical
Data Processing in Peru

As we continue to grapple with the repercussions of the COVID-19 pandemic, the urgency for accelerated and accurate diagnosis of infectious diseases, particularly respiratory illnesses, has become increasingly apparent. Current diagnostic methods, which are often labor-intensive and time-consuming, have been strained under the demands of this global health crisis. This has emphasized the need for innovative diagnostic tools that can streamline and expedite the process.

[Fig 1. Illustration of PROS CXR: ID Model Input and Output]

Artificial Intelligence (AI), with its transformative potential, has emerged as a significant player in this context. AI-driven tools, such as the PROS CXR: ID, developed by Promedius and the Korea Advanced Institute of Science and Technology (KAIST), offer a promising approach to the rapid and effective diagnosis of a wide array of respiratory diseases. These include COVID- 19 induced pneumonia, bacterial pneumonia, and critically, tuberculosis, which continues to present a substantial health burden in Peru.

This project, undertaken by the Universidad de IngenierĂ­a y TecnologĂ­a (UTEC), seeks to enhance the diagnostic accuracy of the PROS CXR: ID through an expansive and meticulous process of medical data collection, refinement, processing, and verification. This process will be focused on both normal and pathological chest X-ray data from Peru, ensuring the data is labeled and verified by medical professionals.

Researcher Co-I:

Julio Ernesto Valdivia Silva

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