Every day, elderly people fall – be it at home or in care facilities. Lindera aims to reduce the risk of falling with the help of artificial intelligence.
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To help patients manage their mental wellness between appointments, researchers at Texas A&M University have developed a smart device-based electronic platform that can continuously monitor the state of hyperarousal, one of the signs of psychiatric distress.
Scientists have assembled a combination of data mining, machine-learning algorithms and compression-based analytics to bring the most useful data to the fore on an office computer.
Bioengineers have designed a glove-like device that can translate American Sign Language into English speech in real time through a smartphone app.
Researchers caution that consumer wearables are not sophisticated enough to monitor the complicated illness.
A portable surveillance device powered by machine learning can detect coughing and crowd size in real time, then analyze the data to directly monitor flu-like illnesses trends.
By adding infrared capability to the ubiquitous, standard optical microscope, researchers hope to bring cancer diagnosis into the digital era.
Researchers from Thomas Jefferson University use machine learning on ultrasound images of thyroid nodules to predict risk of malignancy.