Tag Archives: machine learning

Voice control smart devices might hinder children’s social, emotional development: Study

Voice control devices

Voice control smart devices, such as Alexa, Siri, and Google Home, might hinder children’s social and emotional development, argues an expert in the use of artificial intelligence and machine learning in healthcare, in a viewpoint published online in the Archives of Disease in Childhood. These devices might have long term effects by impeding children’s critical thinking, capacity for empathy and compassion, ...

Read More »

Now using machine learning, find out odors and fragrances

Odour mixtures

Tokyo Institute of Technology researchers have invented a new method that predicts smell based on  the odor impression instead of predicting the smell from molecular features. As the sense of smell is one of the basic senses of animal species, it is critical to finding food, realizing attraction, and sensing danger. Humans detect smells, or odorants, with olfactory receptors expressed ...

Read More »

Super-fast electric car charging is here with Mida’s touch

New Ev charging protocol

Despite the growing popularity of electric vehicles, many consumers still hesitate as it may take longer to power up an electric car than it does to gas up a conventional one. Another concern is that frequent charging or speeding up the charging process can damage the battery and reduce its lifespan. Now, scientists have developed a superfast charging methods tailored ...

Read More »

Improving clinical trials with machine learning

Machine learning could improve our ability to determine whether a new drug works in the brain, potentially enabling researchers to detect drug effects that would be missed entirely by conventional statistical tests, finds a new UCL study published in Brain. “Current statistical models are too simple. They fail to capture complex biological variations across people, discarding them as mere noise. ...

Read More »

Using machine learning to improve patient care

Doctors are often deluged by signals from charts, test results, and other metrics to keep track of. It can be difficult to integrate and monitor all of these data for multiple patients while making real-time treatment decisions, especially when data is documented inconsistently across hospitals. In a new pair of papers, researchers from MIT’s Computer Science and Artificial Intelligence Laboratory ...

Read More »
error: Content is protected !!