A multi-institutional research team is using deep learning for x-ray and CT images to study the long-term progression of COVID-19, thanks to a $3.7 million grant from the National Institutes of Health (NIH).
The researchers, based at Texas A&M University and the University of Iowa, are developing self-supervised deep learning technologies capable of recognizing subtypes of post-COVID lung progression phenotypes. The idea is that understanding these phenotypes helps determine appropriate care measures for long-COVID patients.
The deep-learning model uses x-rays and CT scans to differentiate post-COVID-19 subjects from healthy subjects while simultaneously identifying post-COVID-19 subtypes. The researchers said that using unlabeled images from patients increases the data available to train the model to diagnose and understand disease progression more accurately.
The team is planning a longitudinal human subject study that tracks post-COVID-19 individuals 48 to 60 months after their initial visits to continue building data and developing the model.












![A normal mammogram confirmed by three-year radiologic follow-up illustrates reader-marked regions of interest (ROIs) during (A) unaided (round 1) and (B) artificial intelligence (AI)–assisted (round 2) reading. Each colored dot represents an ROI for recall by a human reader. Readers could mark more than one ROI per case, represented by multiple dots of the same color. During AI-assisted reading, the AI system displayed three visible prompts: two with suspicion of malignancy scores of 35% (left mediolateral oblique [L MLO] and craniocaudal [L CC]) and one with a suspicion of malignancy score of 10% (right craniocaudal [R CC]), shown as polygonal overlays. Without AI, six of 10 readers (60%) marked a false-positive ROI. With AI assistance, this fell to two of 10 (20%). R MLO = right mediolateral oblique.](https://img.auntminnie.com/mindful/smg/workspaces/default/uploads/2026/07/2026-07-14-radiology-mammogram-ai-auto-bias.H0bYO8QlWs.jpg?auto=format%2Ccompress&fit=crop&h=112&q=70&w=112)






