Recent progress in artificial intelligence and machine learning has led to the growth of
research in every aspect of life including the health care domain. However, privacy risks and …

The fusion of blockchain and artificial intelligence (AI) marks a paradigm shift in healthcare,
addressing critical challenges in securing electronic health records (EHRs), ensuring data …

Modeling real-world multidimensional time series can be particularly challenging when
these are sporadically observed (ie, sampling is irregular both in time and across …

The progressive advances in the fifth-generation standard for cellular networks have led to
innovations in the artificial intelligence of things, which have changed the layout of the …

We propose a novel methodology to generate domain-specific large-scale question
answering (QA) datasets by re-purposing existing annotations for other NLP tasks. We …

Predicting the patient's clinical outcome from the historical electronic medical records (EMR)
is a fundamental research problem in medical informatics. Most deep learning-based …

Healthcare systems are transformed digitally with the help of medical technology,
information systems, electronic medical records, wearable and smart devices, and handheld …

Deep learning has recently become very popular on account of its incredible success in
many complex datadriven applications, including image classification and speech …

The main challenge in distributing electronic health records (EHRs) for patient-centered
research, market analysis, medicine investigation, healthcare data mining etc., is data …

With 5G on the verge of being adopted as the next mobile network, there is a need to
analyze its impact on the landscape of computing and data management. In this paper, we …