“If you use A.I. to come up with a new drug, you can make lots and lots of money off that new drug. If you use A.I. to find a new use for an old, inexpensive drug, no one makes any money off of ...

This is Part 1 of Embedded Bias, a series revealing how race-based clinical algorithms pervade medicine and why it's so difficult to change them.. P ediatrician Alexandra Epee-Bounya had had ...

When the ESA (European Space Agency)-led Rosalind Franklin rover heads to Mars no earlier than 2028, a NASA machine learning algorithm gets its first chance to shine after more than a decade of data ...

"TimeMachine," an algorithm developed by U.S. researchers, accurately predicts circadian phase from a single blood sample using gene expression, offering a novel, efficient approach to ...

To accomplish this, we first construct a heterogeneous information network (HIN) that encompasses various biological entities associated with DDAs and their interconnections. Subsequently, we utilize ...

Then there are scarier examples—including health-care algorithms that make errors because they’re trained on only a subset of people (such as white people, those of a specific age range or ...

Code is layed out in subdirectories like this: core/: The core functionality, such as loading matrices, data model, performing experiments etc are exposed as libraries. tools/: Executable scripts ...

Algorithm flow chart of weighted sample elimination. When a sample is eliminated, only the weights of a few samples within its search range need to be adjusted, which means that the weights w ij ...