The Concept of Heart Failure with Machine learning

Every year, nearly one out of eight U.S deaths is caused due to heart failure. One of acute heart failure's most common causes is the presence of excess fluid in the lungs. This condition is known as'pulmonary edema.' A patient's excess fluid level often indicates the doctor's course of action, but such determination requires clinicians to rely on subtle features in X-rays that sometimes lead to inconsistent diagnoses and treatment plans. A group of researchers at MIT's Computer Science and Artificial Intelligence Lab (CSAIL) has developed a machine learning model that can analyse the X-ray to quantify how severe the edema is, on a four-level scale ranging from 0 means healthy to 3 which is very bad.