News by Subject Technology & Engineering

Researchers from MIT and Massachusetts General Hospital have developed an automated model that assesses dense breast tissue in mammograms -- which is an independent risk factor for breast cancer -- as reliably as expert radiologists. This marks the first time a deep-learning model of its kind has successfully been used in a clinic on real patients, according to the researchers. With broad implementation, the researchers hope the model can help bring greater reliability to breast density assessments across the nation.

An artificial intelligence (AI) approach based on deep learning convolutional neural network (CNN) could identify nuanced mammographic imaging features specific for recalled but benign (false-positive) mammograms and distinguish such mammograms from those identified as malignant or negative.

Army researchers are using metallic alloys to lighten the load and enhance the power of Soldier devices used on the battlefield. This research was recently featured on the cover of Advanced Optical Materials.

Army scientists have developed a novel algorithm that enables localization of humans and robots in areas where GPS is unavailable.

Researchers have used a combination of social media and transport data to predict the likelihood that a given retail business will succeed or fail.

MIT researchers have now devised a way to help robots navigate environments more like humans do. Their novel motion-planning model lets robots determine how to reach a goal by exploring the environment, observing other agents, and exploiting what they've learned before in similar situations. A paper describing the model was presented at this week's IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).