British researchers have developed a new artificial intelligence model that can accurately detect lung cancer in its early stages.
A team of doctors, scientists and researchers has developed a new artificial intelligence model that can accurately detect lung cancer in its early stages. This model can lead to faster disease diagnosis and earlier treatment.
Cancer kills nearly 10 million people worldwide every year. In many cases, people’s lives can be saved if the disease is diagnosed in time and treatment is started. Therefore, many scientists want to diagnose this disease in its early stages.
Development of artificial intelligence for cancer diagnosis
The new artificial intelligence was developed by British experts at the Royal March, Institute of Cancer Research, and Imperial College London. This model can determine whether an abnormal growth found in a CT scan is cancerous or not.
According to the researchers, their algorithm is more efficient than the current methods. In the future, they want to enable early detection of cancer so that treatments can be more effective.
The team of scientists used CT scans of nearly 500 patients with large lung nodules to develop their AI algorithm. The method developed by the researchers can extract vital information from medical images that cannot be detected by the human eye.
After development, this artificial intelligence was tested to accurately detect cancerous nodes. In this study, a measure called “area under the curve” (AUC) was used to evaluate the efficiency of artificial intelligence. An AUC of one means the model is perfect, and an AUC of 0.5 means that the model randomly predicts the results.
The researchers’ new artificial intelligence model was able to detect the cancer risk of each node with a value of 0.87 for AUC. The number obtained by this artificial intelligence was higher than the Brock score used in hospitals, 0.67, and a more difficult test called Herder, with a number of 0.83.
Therefore, the researchers’ artificial intelligence model can detect cancer nodes with high accuracy and also help doctors make decisions.
