Many current intrinsically interpretable machine learning models can only handle the data
that are linear, low-dimensional, and relatively independent attributes and often with discrete …

Deep learning requires several design choices, such as the nodes' activation functions and
the widths, types, and arrangements of the layers. One consideration when making these …

Personalized prediction is of high interest in medicine; potential applications include the
prediction of individual drug responses or risks of complications. But typical statistical …

With the improvement of genomic and clinical research facilitated by high-throughput
sequencing methods, it is essential in developing machine learning models that can assist …

The new era of big data is influencing the chemical industry tremendously, providing several
opportunities to reshape its operations. However, given the development of big data, the …