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 …

There has been an increasing interest in translating artificial intelligence (AI) research into
clinically-validated applications to improve the performance, capacity, and efficacy of …

Following unprecedented success on the natural language tasks, Transformers have been
successfully applied to several computer vision problems, achieving state-of-the-art results …

The artificial intelligence revolution has been spurred forward by the availability of large-
scale datasets. In contrast, the paucity of large-scale medical datasets hinders the …

Privacy protection as a major concern of the industrial big data enabling entities makes the
massive safety-critical operation data of a wind turbine unable to exert its great value …

While modern machine learning models rely on increasingly large training datasets, data is
often limited in privacy-sensitive domains. Generative models trained with differential privacy …

The rapid development of Internet of Things (IoT) stimulates the innovation for the health-
related devices such as remote patient monitoring, connected inhalers and ingestible …

Federated learning (FL) allows the collaborative training of AI models without needing to
share raw data. This capability makes it especially interesting for healthcare applications …

Recent advances in computer-aided diagnosis, treatment response and prognosis in
radiomics and deep learning challenge radiology with requirements for world-wide …

This article examines the impact of new AI‐related technologies in data mining and big data
on important research questions in crime analytics. Because the field is so broad, the review …