Researchers from the Neurosciences Research Centre have identified the strengths and limitations of tasks used to detect the early signs of Alzheimer’s through speech analysis and machine-learning.

Google and Verily Life Sciences shared the latest advance in computer vision to identify signs of heart disease. With an accuracy of 70 percent, early results from the AI trained on retinal scan images from more than 200,000 patients is as precise as methods that require blood tests for cholesterol, said Google Brain product manager Lily Peng. It's the latest example of AI being used to tackle the biggest killer in the world: heart disease. It takes more lives than any other cause of death -- 800,000 in the United States alone, according to the American Heart Association. To save lives, an AI army is joining the fight.

And just last week, the data science competition site Kaggle announced the winners of a $1 million contest in which more than 10,000 researchers competed to build machine learning models that could detect lung cancer from CT scans. This is an old idea, dating back to the 1950s, but now that operations like Google and Facebook have access to such enormous amounts of data and computing power, neural networks can achieve far more than they could in the past. Through the Kaggle contest, run in tandem with the tech-minded consultancy Booz Allen, thousands of data scientists competed to build the most accurate neural networks for the task. Before a neural network can start learning the task from a collection of images, trained doctors must label them--that is, use their human intelligence and knowledge to identify the images that show signs of lung cancer.

Shaokang Wang and his startup, Infervision, build algorithms that read X-ray images and identify early signs of lung cancer. The company's technology, Wang says, is already running inside four of the largest hospitals in China. Two are merely running tests, but according to Wang, the two others--Shanghai Changzheng and Tongji, both in Shanghai--are installing the technology across their operations. "It's installed on every doctor's machine," he says. To what extent these doctors are actually using the technology is another question.

Shaokang Wang and his startup, Infervision, build algorithms that read X-ray images and identify early signs of lung cancer. The company's technology, Wang says, is already running inside four of the largest hospitals in China. Two are merely running tests, but according to Wang, the two others--Shanghai Changzheng and Tongji, both in Shanghai--are installing the technology across their operations. "It's installed on every doctor's machine," he says. To what extent these doctors are actually using the technology is another question.