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 …

The importance of big health data is recognised worldwide. Most UK National Health
Service (NHS) care interactions are recorded in electronic health records, resulting in an …

Synthetic data generation is the process of using machine learning methods to train a model
that captures the patterns in a real dataset. Then new or synthetic data can be generated …

Personal (sometimes called “protected”) health information (PHI) is highly valued and will
become centrally important as big data and machine learning move to the forefront of health …

As data-driven science, artificial intelligence (AI) has paved a promising path toward an
evolving health system teeming with thrilling opportunities for precision oncology …

Physicians write clinical notes with abbreviations and shorthand that are difficult to decipher.
Abbreviations can be clinical jargon (writing “HIT” for “heparin induced thrombocytopenia”) …

Generating multivariate time series is a promising approach for sharing sensitive data in
many medical, financial, and IoT applications. A common type of multivariate time series …

Protecting personal health records is becoming increasingly important as more people use
Mobile Health applications (mHealth apps) to improve their health outcomes. These …

Medical artificial intelligence (AI) is considered to be one of the most important assets for the
future of innovative individual and public health care. To develop innovative medical AI, it is …

Conclusions Although a potentially promising application, there are a vast array of technical,
clinical, organizational, and legal concerns that impact the ethics of using machine learning …