Decision Support

LA Children's received the funding to predict how critically ill children handle medication by applying machine learning to identify clinically significant patterns from the ICU data of 20,000 patients. 

Resource constraints and inefficient manual processes are burdening cancer centers across the U.S., but a new report shows how machine learning capabilities outside of EHRs could help improve agility.

A letter from the HIMSS EHR Association outlines concerns and requests clarifications around issues such as automation bias and how the industry would transition away from legacy technologies that conflict with the guidance.

While understanding and reconciling drugs after discharge from the hospital can be challenging, it's a necessity for greater efficacy of care delivery. HL7's Da Vinci project can help.

The cloud-based platform provides security, scale and the processing power needed for genomic data storage and analyses, eliminating the need for specialized infrastructure and workflows.  

Its new Advanced Visualization Workspace includes dozens of clinical apps for cardiology, oncology, neurology and radiology.

The move will make it "simpler for our IT and developers, and will allow them to focus more on uncovering creative ways to improve patient care," said the health system's chief digital information officer.

The new institute will focus on AI and machine learning, virtual and augmented reality, 5G technologies, precision medicine, telehealth and more.

The two-year study uses predictive models, developed for skin cancer diagnosis, to help detect eczema and enable the prevention of future allergies and diseases.

The collaboration builds on clinical research using Numares' machine-driven metabolic diagnostics to enhance care for patients with chronic diseases.