Studies in health technology and informatics
Jun 29, 2022
The accelerating impact of genomic data in clinical decision-making has generated a paradigm shift from treatment based on the anatomic origin of the tumor to the incorporation of key genomic features to guide therapy. Assessing the clinical validity...
Sepsis is a major public health problem and a leading cause of death in the world, where delay in the beginning of treatment, along with clinical guidelines non-adherence have been proved to be associated with higher mortality. Machine Learning is in...
The artificial intelligence (AI) revolution has arrived for the health care sector and is finally penetrating the far-reaching but perpetually underfinanced primary care platform. While AI has the potential to facilitate the achievement of the Quintu...
The rapid growth and decreasing cost of Next-generation sequencing (NGS) technologies have made it possible to conduct routine large panel genomic sequencing in many disease settings, especially in the oncology domain. Furthermore, it is now known th...
The journal of trauma and acute care surgery
Dec 1, 2021
BACKGROUND: Rib fractures serve as both a marker of injury severity and a guide for clinical decision making for trauma patients. Although recent studies have suggested that rib fractures are dynamic, the degree of progressive offset remains unknown....
OBJECTIVE: The aim of this study was to develop and validate a risk prediction tool for trauma-induced coagulopathy (TIC), to support early therapeutic decision-making.
Clinical science (London, England : 1979)
Oct 29, 2021
Ophthalmology has been one of the early adopters of artificial intelligence (AI) within the medical field. Deep learning (DL), in particular, has garnered significant attention due to the availability of large amounts of data and digitized ocular ima...
Machine learning is a tool for analysing digitised data sets and formulating predictions that can optimise clinical decision-making. It aims to identify complex patterns in large data sets and encode them into models that can then classify new unseen...