It is not unusual for doctors to miss radiological abnormalities, and studies have shown an error rate of between 30 and 45%. This is common because of areas on the chest X-ray where lesions can easily be missed: behind the clavicle, heart and diaphragm, at the hilum and pleural lesions. This leads to misdiagnoses and significant delays in initiating the right treatment, resulting in poor patient outcomes such as 1.5 million people worldwide dying each year from medical misdiagnoses.
Our AI solution helps doctors minimise the incidence of missed cases by picking up subtle findings at an early stage. Our deep learning algorithms analyze medical images for features that suggest the presence of diseases. The insights that the analysis results provide to the doctors help reduce the risk of missed diagnosis by up to 20% so as to enable better patient outcomes and save lives.