Smartwatches are among the wearable devices that gather health data. Translating that data into useful information can be complicated and expensive. (iStock) The human body constantly generates a ...

In a future perhaps not too far away, artificial intelligence and its subfield of machine learning (ML) tools and models, ...

Applying Machine Learning (ML) to physiological data poses several challenges. While ML can be effectively used to model well-defined systems, applying it to a system as complex as the human body ...

Strive Health, a value-based kidney care provider, noticed many of its health IT vendors, like the provider itself, operate extensively in the value-based care space and collaborate with accountable ...

Head and neck cancers represent a biologically heterogeneous group of malignancies requiring accurate diagnosis, staging, and risk stratification for ...

In the medical field, alarm fatigue can be a serious issue that directly impacts patient care. When roughly three-quarters of clinical alarms are false, it’s easy to see how this constant overload can ...

Enhancing Readability of Lay Abstracts and Summaries for Urologic Oncology Literature Using Generative Artificial Intelligence: BRIDGE-AI 6 Randomized Controlled Trial We trained and tested ML systems ...

Amazon Web Services is pushing deeper into agentic artificial intelligence for healthcare, taking aim at common administrative tasks such as scheduling, medical histories, clinical documentation and ...

Two of Intermedix’s leading data scientists, Danielle Baghernejad and Lihong Li, have been published in Biomedical Journal of Scientific & Technical Research and Advances in Biotechnology & ...