Cardiac and Vascular Surgery‚ÄďAssociated Acute Kidney Injury: A Fresh New Read!

Abstract Acute kidney injury (AKI) occurs in 7% to 18% of hospitalized patients and complicates the course of 50% to 60% of those admitted to the intensive care unit, carrying […]


Improved Predictive Models for Acute Kidney Injury with IDEAs: Intraoperative Data Embedded Analytics

Acute kidney injury (AKI) is a common and serious complication after a surgery which is associated with morbidity and mortality. The majority of existing perioperative AKI risk score prediction models […]

prisma p icu ai

Our Latest Paper is Available Online!

The Intelligent ICU Pilot Study: Using Artificial Intelligence Technology for Autonomous Patient Monitoring Currently, many critical care indices are repetitively assessed and recorded by overburdened nurses, e.g. physical function or […]

Surgery stock image

The impact of age on the innate immune response and outcomes after severe sepsis/septic shock in trauma and surgical intensive care unit patients.

Abstract Introduction Advancing age is a strong risk factor for adverse outcomes across multiple disease processes. However, septic surgical and trauma patients are unique in they incur two or more […]

Figure 4. Similarities and redundancies in the pathophysiology of patients with sepsis, cancer, and advanced age.

Innate Immunity in the Persistent Inflammation, Immunosuppression, and Catabolism Syndrome and Its Implications for Therapy.

Innate Immunity in the Persistent Inflammation, Immunosuppression, and Catabolism Syndrome and Its Implications for Therapy Clinical and technological advances promoting early hemorrhage control and physiologic resuscitation as well as early […]

DeepSofa Acuity Scores

Our DeepSofa draft is available online!

  DeepSOFA: A Real-Time Continuous Acuity Score Framework using Deep Learning Traditional methods for assessing illness severity and predicting in-hospital mortality among critically ill patients require manual, time-consuming, and error-prone […]

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Established in 2013, PrismaP is changing the face of medicine through the use of intelligent, data-driven algorithms.

Bringing together experts in Medicine, Health Policy Research, and Computer Engineering, our partnership combines modern approaches to modeling, signal processing, and machine learning in order to develop and refine data analysis methods. The predictive models, physiologic markers and clinical reasonings generated by Prisma P will serve to facilitate patient care in perioperative environments.