When It Comes to Health Care, AI Has a Long Way to Go Back Medical information is more complex and less available than the web data that many algorithms were trained on, so results can be misleading. THE CORONAVIRUS PANDEMIC has prompted countless acts of individual heroism and some astounding collective feats of science. Pharmaceutical companies…
Bitcoin: The Power to Unlock Financial Freedom Back Bitcoin education can empower those who have been left behind by legacy financial services. Bitcoin is about people, not price. While the U.S. continues to focus on bitcoin as an investment asset, other parts of the world are showing us the true use cases of Bitcoin. In…
Common pitfalls and recommendations for using machine learning to detect and prognosticate for COVID-19 using chest radiographs and CT scans Back Abstract Machine learning methods offer great promise for fast and accurate detection and prognostication of coronavirus disease 2019 (COVID-19) from standard-of-care chest radiographs (CXR) and chest computed tomography (CT) images. Many articles have been…
Back Opening the Duke electronic health record to apps: Implementing SMART on FHIR Highlights • The SMART on FHIR framework is a novel tool for EHR interoperability. • A custom integration of SMART on FHIR with the Epic EHR is demonstrated. • Several provider and patient apps are successfully integrated using this technique. • Security…
Back to homepage Abstract Final version accepted 12 January 2021 Objective To review and appraise the validity and usefulness of published and preprint reports of prediction models for diagnosing coronavirus disease 2019 (covid-19) in patients with suspected infection, for prognosis of patients with covid-19, and for detecting people in the general population at increased risk of covid-19…