Artificial Intelligence Radiology (AIR). A co-pilot tool for quantitat. assessment of lung diseases

Purpose and goal

The AIR project aims to assist radiologists in longitudinal assessments of lung diseases. Its goals include: 1.Developing an AI tool that enables objective measures of predominant lung disease based on Computed Tomography images and laboratory results. 2.Assisting radiologists in making precise diagnoses and giving insights into disease patterns, treatment efficacy and personalized care. 3.Promoting international collaboration that addresses public health by evaluating the impact of biomarker data collection through self-sampling.

Expected effects and result

The AIR project aims to reduce the variability arising from subjective interpretations of lung exams. The solution is expected to lead to more equitable access to accurate diagnoses and treatments, thereby helping to bridge healthcare disparities within the population. The project benefits all participants by offering: Improved diagnostic accuracy Enhanced product portfolios Validation of expertise Opportunities for research and educational advancement Fostering international cooperation between Sweden and Brazil

Planned approach and implementation

This multidisciplinary collaboration involves Brazilian and Swedish actors in the healthcare sector. The participants include InLab (InRad), Capitainer, CERTI Foundation, Philips Healthcare, and Halmstad University members. The project encompasses six working packages implemented over a three-year timeline. The tasks are creating AI models based on computed tomography scans while enabling blood sampling for convenient testing and reliability of the entire system.