The increasing availability of biomedical data from large biobanks, electronic health records,
medical imaging, wearable and ambient biosensors, and the lower cost of genome and …

Artificial intelligence (AI) systems hold great promise to improve healthcare over the next
decades. Specifically, AI systems leveraging multiple data sources and input modalities are …

Multimodal data-driven approach has emerged as an important driving force for smart
healthcare systems with applications ranging from disease analysis to triage, diagnosis and …

Biomedical data are becoming increasingly multimodal and thereby capture the underlying
complex relationships among biological processes. Deep learning (DL)-based data fusion …

Precision medicine is an emerging approach to clinical research and patient care that
focuses on understanding and treating disease by integrating multi-modal or multi-omics …

Digital health data are multimodal and high-dimensional. A patient's health state can be
characterized by a multitude of signals including medical imaging, clinical variables …

Highlights•Big Data are radically transforming Personalized Medicine.•Multi-omics, images,
device data, and electronic health records represent the main big data types in biomedical …

Advances in computational and data sciences for data management, integration, mining,
classification, filtering, visualization along with engineering innovations in medical devices …

Recent advances in high-throughput technologies have led to the emergence of systems
biology as a holistic science to achieve more precise modeling of complex diseases. Many …

Digital transformation is impacting every facet of science and society, not least because
there is a growing need for digital services and products with the COVID-19 pandemic. But …