Federated learning (FL) has drawn increasing attention owing to its potential use in large-
scale industrial applications. Existing FL works mainly focus on model homogeneous …

Genome sequencing and analysis allow researchers to decode the functional information
hidden in DNA sequences as well as to study cell to cell variation within a cell population …

The exponential growth of big data in RNA biology (RB) has led to the development of deep
learning (DL) models that have driven crucial discoveries. As constantly evidenced by DL …

Computed tomography (CT) is of great importance in clinical practice due to its powerful
ability to provide patients' anatomical information without any invasive inspection, but its …

Modern machine learning models toward various tasks with omic data analysis give rise to
threats of privacy leakage of patients involved in those datasets. Here, we proposed a …

Digital and remote technologies (DRT) are increasingly being used in scientific
investigations to objectively measure human behavior during day-to-day activities. Using …

The magnitude, complexity, and diversity of cyber threats against the Internet of Medical
Things have increased over the past several years, making it challenging to implement …

In clinical practice, computed tomography (CT) is an important noninvasive inspection
technology to provide patients' anatomical information. However, its potential radiation risk is …

Widespread generation and analysis of omics data have revolutionized molecular medicine
on Earth, yet its power to yield new mechanistic insights and improve occupational health …

Advances in genomics are increasingly depending upon the ability to analyze large and
diverse genomic data collections, which are often difficult to amass due to privacy concerns …