Using Artificial Intelligence in Fungal Lung Disease: CPA CT Imaging as an Example
Elsa D. Angelini, Anand Shah
Abstract
This positioning paper aims to discuss current challenges and opportunities for artificial intelligence (AI) in fungal lung disease, with a focus on chronic pulmonary aspergillosis and some supporting proof-of-concept results using lung imaging. Given the high uncertainty in fungal infection diagnosis and analyzing treatment response, AI could potentially have an impactful role; however, developing imaging-based machine learning raises several specific challenges. We discuss recommendations to engage the medical community in essential first steps towards fungal infection AI with gathering dedicated imaging registries, linking with non-imaging data and harmonizing image-finding annotations.
Topics & Concepts
Lung diseaseMedical imagingFungal diseaseMedical physicsArtificial intelligenceAspergillosisComputer scienceLungPathologyData scienceRadiologyMedicineImmunologyDermatologyInternal medicineAntifungal resistance and susceptibilityLung Cancer Diagnosis and TreatmentMedical Imaging Techniques and Applications