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Smart AI for diagnosing Idiopathic Pulmonary Fibrosis

Technologies: Python, Docker, Image Segmentation, Deep Learning
AI
Smart AI for diagnosing Idiopathic Pulmonary Fibrosis
Smart AI for diagnosing Idiopathic Pulmonary Fibrosis
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1. BACKGROUND & ISSUES
What is Idiopathic Pulmonary Fibrosis (IPF)? It's a condition in which the lungs gradually lose respiratory function and the cause of the disease is unknown. IPF is a lung disease that is often fatal and difficult to diagnose, so far there are no accurate data on the number of people affected. As of 2020, there are approximately 180,000 cases of IPF in the United States, and 40,000 people died from the disease each year. In addition, in 2020 in the United States, the number of traffic accident deaths was 38,680 people, which was recorded as the highest level in 13 years, but this number is still lower than the number of people died from the disease.
2. FEATURES & SOLUTIONS
Usually, the average survival time of a patient is about 3 years from the time of diagnosis. However, advanced AI technology can diagnose IPF early and accurately. As a result, patients with the disease have more time, more chances for treatment and prolong survival. The algorithm predicts the likelihood of survival, and provides a treatment plan for the patient.
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