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
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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
Performance of a Standardized Clinical Assay for Urinary C-C Motif Chemokine Ligand 14 (CCL14) for Persistent Severe Acute Kidney Injury
CONCLUSIONS: Using a clinical assay, these standardized cutoffs (1.3 and 13 ng/ml) allow for the identification of patients at high risk for the development of persistent severe AKI. These results…
Early differentiation between sepsis and sterile inflammation via urinary gene signatures of metabolic dysregulation
CONCLUSIONS: Whole-genome transcriptomic profiling of urinary cells revealed focused probe panels that can function as an early diagnostic tool for differentiating sepsis from sterile SIRS. Functional analysis of differentially expressed…
Association of Renin Angiotensin Aldosterone System Inhibitors and Outcomes of Hospitalized Patients With COVID-19
CONCLUSIONS: Among patients hospitalized for COVID-19 who were taking AHAs, prior use of a combination of RAASIs and other AHAs was associated with higher in-hospital mortality than the use of…
Postoperative Overtriage to an Intensive Care Unit Is Associated With Low Value of Care
CONCLUSIONS: Low-acuity postoperative patients who were overtriaged to ICUs had increased total costs, no improvements in outcomes, and received low-value care.