Understanding the tremendous potential of AI to cut physicians’ workloads and reduce time to diagnosis, AltexSoft invested effort in creating a prototype of a decision support tool for chest X-ray analysis. It aimed to perform three machine learning tasks: lung segmentation to identify the boundaries of lungs; lung disease classification to predict a probability of pneumonia, fibrosis, and pneumothorax; and pneumothorax (collapsed lung) mask creation to localize this dangerous condition if detected.
The tool targets both medical experts and patients, serving as a source of a second opinion about the presence of lung abnormalities. If required, the functionality can be relatively quickly extended to more disorders and non-X-ray medical imaging, primarily CT scans.
The prototype was completed in 2 months by a team of 4 experts: 2 ML engineers, 1 software engineer, and 1 UX/UI designer. The total human effort amounted to 4-5 person/month.
The technology stack comprised Python, the aiohttp package, Docker, React, and JavaScript. As for the machine learning stack, it included U-Net, EfficientNet, Feature Pyramid Network (FPN), PyTorch, Albumentations, and OpenCV.