High-throughput profiling methods (such as genomics or imaging) have accelerated basic
research and made deep molecular characterization of patient samples routine. These …

Synthetic health data have the potential to mitigate privacy concerns in supporting
biomedical research and healthcare applications. Modern approaches for data generation …

Background Artificial intelligence (AI) methods are becoming increasingly commonly
implemented in healthcare as decision support, business intelligence tools, or, in some …

Background Hospital readmissions for pneumonia are a growing concern in the US, with
significant consequences for costs and quality of care. This study developed the rule-based …

Increased values of the FIB-4 index appear to be associated with poor clinical outcomes in
COVID-19 patients. This study aimed to develop and validate predictive mortality models …

The role of informatics in public health has increased over the past few decades, and the
coronavirus disease 2019 (COVID-19) pandemic has underscored the critical importance of …

Objective To evaluate the ability of a neural network to identify severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) infection using point-of-care electrocardiography …

Over the past few decades, information about patients' diagnoses, medication, and
procedures has been collected and transformed into standardized and shareable electronic …

Objective The evaluation of natural language processing (NLP) models for clinical text de-
identification relies on the availability of clinical notes, which is often restricted due to privacy …

Computational interpretation of human genetic variants comprises the development and
application of analysis and prediction techniques aimed at elucidating the impact of variants …