With the increasing availability of rich, longitudinal, real-world clinical data recorded in
electronic health records (EHRs) for millions of patients, there is a growing interest in …

Cells are essential to understanding health and disease, yet traditional models fall short of
modeling and simulating their function and behavior. Advances in AI and omics offer …

Virtual patients and digital patients/twins are two similar concepts gaining increasing
attention in health care with goals to accelerate drug development and improve patients' …

Neuroimaging, across positron emission tomography (PET), electroencephalography (EEG),
and magnetic resonance imaging (MRI), has been a mainstay of clinical neuroscience …

Despite the wealth of single-cell multi-omics data, it remains challenging to predict the
consequences of novel genetic and chemical perturbations in the human body. It requires …

Currently, information on the toxicity profile of the majority of the identified e‐waste
chemicals, while extensive and growing, is admittedly fragmentary, particularly at the cellular …

The healthcare industry has witnessed significant interest in applying DTs (DTs), due to
technological advancements. DTs are virtual replicas of physical entities that adapt to real …

This chapter explores the effective communication of digital twin technology's value to
healthcare executives. It identifies the critical role that healthcare managers play in …

Given advancements in large-scale data and AI, integrating multimodal artificial intelligence
into cancer research can enhance our understanding of tumor behavior by simultaneously …

Digital twins have recently emerged in healthcare. They combine advances in cyber–
physical systems, modelling and computation techniques, and enable a bidirectional flow of …