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.

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 Ingeniería y Tecnología (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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