innovation in medicine
Making New Discoveries
There is always exciting research being conducted at PRISMAp labs. Find out more about our exciting research or read one of our many published articles below.
Current Projects
- Motion Analysis of Delirium in the Intensive Care Unit (ICU)
- Intelligent ICU of the Future
- Integrating Data, Algorithms and Clinical Reasoning for Surgical Risk Assessment (IDEALIST)
- Automated Algorithm Identifies and Communicates Risk of Acute Kidney Injury among Health Care Providers and Patients (AKI-EPIC)
- Network Analysis of Urinary Molecular Signature Complements Clinical Data to Predict Postoperative Acute Kidney Injury (NavigateAKI) clinicaltrials.gov
- Digital Rehabilitation Environment Augmenting Medical System (DREAMS) clinicaltrials.gov
Follow PRISMAp on Twitter for the latest research updates!
Featured Publications
Human Activity Recognition Using Inertial, Physiological, and Environmental Sensors
This survey focuses on critical role of machine learning in developing Human Activity Recognition applications based on inertial sensors in conjunction with physiological and environmental sensors.
Discovery and Validation of Urinary Molecular Signature of Early Sepsis
The first ever study to use urinary cellular gene expression to study sepsis. Researchers identified alterations in gene expression unique to systemic and kidney-specific pathophysiologic processes using whole-genome analyses of RNA isolated from the urinary cells of sepsis patients.
Clinical Trajectories of Acute Kidney Injury in Surgical Sepsis: A Prospective Observational Study
Among critically ill surgical sepsis patients, persistent AKI and the absence of renal recovery are associated with distinct early and sustained immunologic and endothelial biomarker signatures and decreased long-term physical function and survival.
Audiovisual Modules to Enhance Informed Consent in the ICU: A Pilot Study
Audiovisual modules may improve knowledge and comprehension of commonly performed ICU procedures among critically ill patients and caregivers who have no healthcare background.
Extended vertical lists for temporal pattern mining from multivariate time series
In this paper, the problem of mining complex temporal patterns in the context of multivariate time series is considered. A new method called the Fast Temporal Pattern Mining with Extended Vertical Lists.
Reinforcement learning in surgery
Patients and physicians make essential decisions regarding diagnostic and therapeutic interventions. These actions should be performed or deferred under time constraints and uncertainty regarding patients’ diagnoses and predicted response to treatment. This may lead to cognitive and judgment errors.
Our Latest Publications
Early combination therapy with immunoglobulin and steroids is associated with shorter ICU length of stay in Multisystem Inflammatory Syndrome in Children (MIS-C) associated with COVID19: A retrospective cohort analysis from 28 U.S Hospitals
CONCLUSIONS: Combination therapy with IVIG and steroids initiated in the first 2 days of admission favorably impacts ICU but not the overall hospital LOS in children with MIS-C.
Gamification for Machine Learning in Surgical Patient Engagement
Patients and their surgeons face a complex and evolving set of choices in the process of shared decision making. The plan of care must be tailored to individual patient risk…
Potentials and Challenges of Pervasive Sensing in the Intensive Care Unit
Patients in critical care settings often require continuous and multifaceted monitoring. However, current clinical monitoring practices fail to capture important functional and behavioral indices such as mobility or agitation. Recent…
Performance of a Machine Learning Algorithm Using Electronic Health Record Data to Predict Postoperative Complications and Report on a Mobile Platform
CONCLUSIONS AND RELEVANCE: In this study, automated real-time predictions of postoperative complications with mobile device outputs had good performance in clinical settings with prospective validation, matching surgeons’ predictive accuracy.