LookDeep has recently published articles on the pivotal role of hospital security in telemedicine systems within the healthcare sector. At LookDeep, our commitment to security has been fundamental to our mission from day one, and we’ve consistently emphasized its significance through our numerous publications. With the increasing focus on telemedicine security and related issues, its […]
I was honored to give a talk at Society for Hospital Medicine Converge 2023. The talk discussed our successful collaboration with UCSF that demonstrated the feasibility and utility of an artificial intelligence-powered computer vision camera to monitor patients at high risk of delirium. We were excited by the ability to capture activity patterns that are […]
Given the importance of the overnight period in inpatient care, it remains challenging to get objective, quantitative data on whether or not a patient had a good night. And, to be provocative: how do we even define what is meant by a “good night?” While there is growing awareness that patients very often have sleepless […]
This work builds on our initial research in AI computer vision in the Duke medical intensive care unit. This research demonstrated several compelling data-driven readouts of patient activity and room environment, highlighting its potential utility in sleep, sedation, agitation, and delirium
“We are excited about our collaboration with LookDeep to use AI to expand virtual safety, nursing and medical services to support our staff and improve patient care,” said Dr. Paul DePriest, Executive Vice President and Chief Operating Officer for Baptist Memorial Health Care.
In this blog post, I review LookDeep Health’s IRB-approved collaboration with Oregon Health Sciences University (OHSU) on AI-enabled computer vision monitoring of trauma patients at-risk for delirium.
Inpatient video has massive potential as a new form of patient monitoring and as a new kind of medical data type. One obstacle to overcome to realize this potential is the fact that video generates massive amounts of data, way more than any human can interpret (much less clinicians who are pressed for time taking care of sick patients).
Monitoring patient activity in the ICU is essential for sedation management, identifying agitation, and diagnosing delirium. Despite its importance in ICU care, activity monitoring is intermittent, subjective, and qualitative.
