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Extracorporeal membrane oxygenation (ECMO) is among the most resource-intensive therapies in critical care. The COVID-19 pandemic highlighted the lack of ECMO resource allocation tools. We aimed to develop a continuous ECMO risk prediction model to enhance patient triage and resource allocation.

In the general hospital wards, machine learning (ML)-based early warning systems (EWSs) can identify patients at risk of deterioration to facilitate rescue interventions. We assess subpopulation performance of a ML-based EWS on medical and surgical adult patients admitted to general hospital wards.

The continuous integration of artificial intelligence (AI) into clinical settings requires the development of up-to-date and robust guidelines and standard frameworks that consider the evolving challenges of AI implementation in medicine. This review evaluates the quality of these guideline and summarizes ethical frameworks, best practices, and recommendations.

To compare various methods for extracting daily dosage information from prescription signatures (sigs) and identify the best performers.

To pilot a digital health technologies ecosystem known as project SingaporeWALK (Wearables and Apps for Community Living and Knowledge) that build capacity in older adults, senior center managers, health coaches, and caregivers in using health technologies (eg, wearables, apps, exergames) collaboratively in a gamified way for active aging.

Statistical and artificial intelligence algorithms are increasingly being developed for use in healthcare. These algorithms may reflect biases that magnify disparities in clinical care, and there is a growing need for understanding how algorithmic biases can be mitigated in pursuit of algorithmic fairness. We conducted a scoping review on algorithmic individual fairness (IF) to understand the current state of research in the metrics and methods developed to achieve IF and [...]

In recent years, the rise of big data and artificial intelligence has led to an increasing expansion of databases and web services in biomedical research. cBioPortal is one of the most widely used platforms for accessing cancer genomic and clinical data. The primary objective of this study was to develop a tool that simplifies programmatic interaction with cBioPortal's web service.

To improve performance of medical entity normalization across many languages, especially when fewer language resources are available compared to English.

To develop indices of US hospital interoperability to capture the current state and assess progress over time.

To detect and classify features of stigmatizing and biased language in intensive care electronic health records (EHRs) using natural language processing techniques.