Medical image is a very important part of diagnosis and decision making for a doctor. More than 5 Billion imaging studies are requested globally in a year, these images include X-Ray, CT and MRI. A major portion of the diagnosis is manual process and with the increase in the patient volume, due to the stressed demand the diagnostic errors play a role in up to 10% of patient deaths, and between 3% and 6% of image interpretations.

One prominent case is medical image analysis is Progressive ILDs, characterized by deteriorating lung function and are usually fatal. Their causes largely remain a mystery. More than 200 different lung diseases are classified in this group, and they affect a large group of individuals: It is estimated that more than 10 cases per 100000 are diagnosed with idiopathic interstitial lung diseases each year.

Early detection has proved to arrest the progression of the disease and in many cases cure them.

Partnered with leading academic medical centers, large global Hospitals, diagnostic centers, involving leading radiologists, pulmonologists and data science experts, the aim is to speed diagnosis, aid prognosis, and provide therapy progress and feedback to patients battling ILDs.

DASA labs is using artificial intelligence to provide deep insights on these diseases, by applying deep learning algorithms to find patterns in a carefully selected, large number of high-resolution CT scans. The goal is more importantly to gain clarity in the interrelationships behind the images of the illnesses, apply in facilitating the care giver in more accurate diagnosis. Also provide a longitudinal view for progress tracking.