Helping COVID-19 Patients Understand their X-Rays Better

QNRF-funded technology helps predict disease progression and recovery

Have you ever sat feeling clueless in front of a doctor, while they hold your X-ray and explain their observations? Cluelessness, coupled with nervousness, often makes the experience of an X-ray diagnosis an unpleasant one for the patient.

Dr. Yin Yang, now an Associate Professor in the College of Science and Engineering at Hamad Bin Khalifa University, had a similar experience in his 20s when he was hospitalized for a week due to pneumonia. Put under observation, he was not allowed to meet any visitors and could not get hold of the medical staff to explain his condition in detail in a way that he could understand, so that he could find out how long he would take to recover.

After spending a week feeling depressed and confused, Dr. Yang was discharged, but his experience at the hospital left him perturbed. He decided to dig deeper and explore how such an unnerving experience could be made more comfortable and patient-friendly.

Some investigation revealed that, from the doctor’s point of view, Dr. Yang’s condition was under control, and, based on his assessment of the chest X-ray scans, the recovery process was expected to be smooth.

Through his experience, Dr. Yang found a silver lining; he started to question how complex medical information could be conveyed to a patient without a medical background. Moreover, while under treatment, could there be a way for the patient to see the predicted disease progression in the future?

Due to the unique proposed outcomes of the project, which could help COVID-19 patients monitor their progress, the project titled, 'Predicting and Visualizing COVID-19 Patients’ Future Chest X-Ray Images with Deep Learning' (RRC-2-117), passed the highly competitive screening rounds and was selected for funding earlier this year.

Over the next three months, Dr. Yang and his team worked tirelessly to develop a cutting-edge prototype based on an AI system. This innovative system can predict future chest X-ray scan results and can render and annotate a series of X-ray images to clearly visualize disease progression.

One of the benefits this project presents is that patients can take better care of themselves, having a realistic idea of their condition and the recovery timeline. Moreover, such a system could help not only the patient, but also the patient’s family, caretakers, and healthcare professionals by avoiding giving them unnecessary worry.

Dr. Yang and his team plan to take this project a step further and make it a ready-to-use product for patients and healthcare professionals. One idea that the team is pursuing is accelerating the AI mode, so it can run smoothly on a compatible laptop or even a smartphone. Therefore, thanks to this technology, patients will no longer have to sit feeling clueless in front of a doctor. End-users will be able to scan their X-ray image onto their phone with ease, analyze it with a custom-built app, and observe a series of images visualizing a predicted recovery plan.

Owing to its successful outcomes, this project successfully advances QNRF’s mission to offer the best healthcare service for residents of Qatar, especially in emergent situations, such as the coronavirus, and to project Qatar as an emerging center of innovation in the medical sector in the region.