Coordinating complicated interactive systems, whether it's the different modes of transportation in a city or the various ...

It can be relatively cheap to gather a lot of bio-signal data. To teach a machine-learning algorithm ... In this case, we’re training the algorithm to predict when that heartbeat will occur.

and explaining to users an algorithm’s capabilities and limitations including the characteristics of the training data set. Caution should be employed with new technology. What are the risks with the ...

In a new article, researchers have studied the impact of a popular machine-learning pricing ... have proprietary algorithms that use large amounts of data to estimate property values.

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

Machine learning algorithms, adept at sifting through voluminous ... Models, ranging from traditional DT to NN, are trained and fine-tuned on a data subset to optimize predictive capabilities.

mRNA microarray data was used to explore the molecular features of AKI. We further identified the AKI signature using machine learning. Finally, we validated these potential biomarkers via an in vitro ...