Scientists and clinicians are starting to translate genomic discoveries from research labs to
the clinical setting. In the process, big data genomic technologies are both a risk to …

1 Whether this data availability is technologically shaped as data pooling or as federated
learning is not decisive for our argument here. The draft regulation of the European …

In the contemporary digital landscape, the exchange of patient data plays a pivotal role in
enhancing healthcare outcomes, fostering research advancements, and promoting public …

While interest in the application of machine learning to improve healthcare has grown
tremendously in recent years, a number of barriers prevent deployment in medical practice …

Trial registration, results disclosure, and sharing of analyzable individual participant data
(IPD) are considered powerful tools for achieving higher levels of transparency and …

Background Greater transparency and, in particular, sharing of patient-level data for further
scientific research is an increasingly important topic for the pharmaceutical industry and …

Accurate and consistent reporting of medical terms in clinical trials is imperative to ensure
data integrity and human subjects protection as decreed by global regulatory agencies …

Clinical trials are fundamental to the advancement of medical science, serving as pivotal
platforms for evaluating the safety and efficacy of new treatments and therapies. Central to …

The application of artificial intelligence and machine learning (ML) technologies in
healthcare have immense potential to improve the care of patients. While there are some …

Studies on the ethics of automating clinical or research decision making using artificial
intelligence and other algorithmic tools abound. Less attention has been paid, however, to …