Machine learning can also be used for preventative care, such as identifying risk factors for ... healthcare to diagnose diseases. For example, Google has developed an algorithm that can detect ...

People living with HIV who have taken highly active antiretroviral therapy can have hyperlipidemia predicted in advance by ...

In livestock, veterinary drug residues are detected through non-destructive methods like hyperspectral imaging. One case in ...

And their method could even be used to find new genetic markers of heart disease that existing ... the researchers used a machine learning algorithm called an autoencoder, which automatically ...

Many of these devices are powered by machine-learning algorithms fueled with ... improve the early detection of heart disease. Guidelines ultimately can influence payers and spur the creation ...

By improving pretraining, we are making machine-learning algorithms better and more efficient at detecting diseases and disorders. Pretraining improvements reduce costs and the amount of experts ...

His scholarly opus, titled "Predictive Modeling of Environmental Impact on Non-Communicable Diseases and Neurological ... underpinned by advanced machine-learning algorithms.

But when researchers used a machine learning algorithm ... linked to the disease conditions themselves." Microbial load has long been recognized as an important factor in microbiome research ...

But when researchers used a machine learning algorithm to predict ... was a key factor for bacterial signatures in fecal samples, even in disease patients. "We were surprised to find that many ...

Using machine learning approaches ... To develop more efficient health guidance, it is important to identify factors that influence its effectiveness (e.g., characteristics and lifestyle of ...