Doctors believe artificial intelligence is now saving lives after a major advancement in breast cancer screenings. AI is detecting early signs of the disease, in some cases years before doctors would find the cancer on a traditional scan. Artificial intelligence is reportedly advancing work in the fight against cancer. Dr. Laurie Margolies, chief of breast imaging at Mount Sinai Health System, told CBS News this week the technology is being used to detect breast cancer. "I think artificial intelligence has the ability to make us be even better physicians than we might otherwise be, by teaching us what are the risk factors, what makes a certain pattern of breast tissue be at high risk," she explained, noting that AI can see things the naked eye might miss on a mammogram.

A new artificial intelligence tool can accurately identify cancer in a development doctors and scientists said could speed up diagnosis of the disease. The algorithm performs more effectively than current methods, according to a study. It can identify whether abnormal growths found on CT scans are cancerous. The AI tool, designed by experts at the Royal Marsden NHS foundation trust, the Institute of Cancer Research, London, and Imperial College London, could fast-track patients to treatment. A new artificial intelligence tool can accurately identify cancer in a development doctors and scientists said could speed up diagnosis of the disease.

The robot is still 5 to 10 years away from showing up in a clinical setting, researchers said, but the device comes on the heels of a fleet of other robotic innovations allowing doctors the ability to better scan a patient's lungs for cancerous tissue. They are designed to ease a task doctors have long struggled with: reaching the inner recesses of the human body, for diagnostic and treatment purposes, without causing damage or using invasive procedures.

A contest aimed at automating the detection of lung cancer shows how machine learning may be poised to overhaul medical imaging. The challenge offered $1 million in prizes for the algorithms that most accurately identified signs of lung cancer in low-dose computed tomography images. The winning algorithms won't necessarily be adopted by clinicians, but they could inspire algorithmic innovations that find their way into medical imaging. Low-dose CT scans have shown great potential in recent years for detecting lung cancer earlier. They use less radiation and do not require a contrast dye to be injected into the body.

A contest aimed at automating the detection of lung cancer shows how machine learning may be poised to overhaul medical imaging. The challenge offered $1 million in prizes for the algorithms that most accurately identified signs of lung cancer in low-dose computed tomography images. The winning algorithms won't necessarily be adopted by clinicians, but they could inspire algorithmic innovations that find their way into medical imaging. Low-dose CT scans have shown great potential in recent years for detecting lung cancer earlier. They use less radiation and do not require a contrast dye to be injected into the body.