​​The AIR project is led by Halmstad University and brings together healthcare stakeholders from Sweden and Brazil, including InRad, the Brazilian radiological institute, Philips Healthcare, and the CERTI Foundation at EMBRAPII. The project aims to create a model for more equal and accessible healthcare globally by combining AI-based image analysis and laboratory diagnostics through self-sampling.

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The project’s two main areas are developing an AI-based algorithm to analyze computed tomography (CT) images and enabling easier blood sampling for patients with limited access to healthcare. As part of this project, analyses for blood markers used in lung diagnostics are being developed based on Capitainer’s self-sampling technology, enabling patients to collect blood samples at home and send them to laboratories for analysis. The algorithm provides radiologists with an effective tool to monitor disease progression over time and adapt care according to patient needs. Through AI, assessments can be standardized, reducing the subjectivity that often occurs when radiologists interpret images. This enables more accurate and reliable monitoring of the patient’s condition. Capitainer’s technology complements image analysis by adding biomarker data from blood samples, which can provide more comprehensive and precise diagnosis and follow-up.

This collaboration enables healthcare professionals to get a more objective and detailed picture of the patient’s condition over time, which not only improves diagnostics but can also provide more reliable data for treatment and follow-up.

“By bringing together AI-based image analysis with Capitainer’s self-sampling technology, we are opening up opportunities to create a new standard for how we monitor and manage lung diseases. This collaboration enables healthcare professionals to get a more objective and detailed picture of the patient’s condition over time, which not only improves diagnostics but can also provide more reliable data for treatment and follow-up,” says Fábio Gama, Associate Professor in Healthcare Innovation at Halmstad University.

The project receives funding from EMBRAPII, a Brazilian research institution, and the Swedish innovation agency Vinnova.