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
ADAPT
Autonomous Delirium Monitoring and Adaptive Prevention
Delirium prevention in the ICU is often achieved with non-pharmacological approaches, but some methods are difficult to implement due to their dependence on sporadic human observations. ADAPT, the Autonomous Delirium Monitoring and Adaptive Prevention system, will autonomously quantify two indicators of delirium (patient mobility and circadian desynchrony) and predict delirium trajectories, as well as prompt actions that decrease delirium risk factors (e.g., ambient light, nightly disruptions). Successful application of ADAPT would augment clinical decision-making and promote more targeted interventions.

CHoRUS (Bridge2ai)
A Patient-Focused Collaborative Hospital Repository Using Standards (CHoRUS) for Equitable AI
While AI in critical care (AICC) has helped improve patient care, AICC research lacks a large generalized dataset, standards that support the exchange and use of health information (interoperability) between sites and researchers, and support from a workforce trained in AI and general public familiar with medical AI. CHoRUS, a multimillion dollar collaboration of 18 top medical research institutions, aims to solve these problems by creating a 100,000 patient dataset from a sample population with varied backgrounds, ethical standards that enable interoperability, and AI education for AICC researchers and the general public.

Intelligent Intensive Care Unit (I2CU)
Pervasive Sensing and Artificial Intelligence for Augmented Clinical Decision-Making
Although close monitoring and dynamic assessment of patient acuity are key aspects of ICU care, both are limited by time constraints imposed on healthcare providers. Dynamic and precise assessment of patient acuity relies almost exclusively on physicians’ clinical judgement and vigilance, and details indicating patient condition may be partially captured or completely missed by overburdened nurses. We aim to develop deep learning models for sensing, quantifying, and communicating any patient’s condition in an autonomous, precise, and interpretable manner. This tool could enhance clinical workflow and enable early intervention.

IDEALIST
Integrating Data, Algorithms, and Clinical Reasoning for Surgical Risk Assessment
IDEALIST could advance the ability of healthcare providers to diagnose diseases by computing the risk of postoperative complications in real-time. Ultimately, the results are expected to improve patient outcomes, decrease hospitalization costs, and reduce lifelong complications. The proposed research is relevant to public health because it can result in enhanced perioperative care workflow and early intervention.

MEnD-AKI
Multi-Hospital Electronic Decision Support for Drug-Associated AKI
The Multi-Hospital Electronic Decision Support for Drug-Associated AKI (MEnD-AKI) project is aimed at assessing how effective a clinical surveillance system augmented with real-time predictive analytics can be in supporting pharmacist-led interventions to address drug-associated AKI (D-AKI).

Additional Projects
- 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
Machine Learning-Enabled Clinical Information Systems Using Fast Healthcare Interoperability Resources Data Standards: Scoping Review
CONCLUSIONS: Shortcomings in current ML-CISs can be addressed by incorporating modular and interoperable data management, analytic platforms, secure interinstitutional data exchange, and application programming interfaces with adequate scalability to support…
Challenges in Pharmacovigilance: Variability in the Criteria for Determining Drug-Associated Acute Kidney Injury in Retrospective, Observational Studies
CONCLUSION: This review highlights the substantial variability in D-AKI criteria in select studies. Minimum expectations about what should be reported and criteria for the elements reported are needed to assure…
Digital health and acute kidney injury: consensus report of the 27th Acute Disease Quality Initiative workgroup
Acute kidney injury (AKI), which is a common complication of acute illnesses, affects the health of individuals in community, acute care and post-acute care settings. Although the recognition, prevention and…
The Persistent Inflammation, Immunosuppression, and Catabolism Syndrome (PICS) Ten Years Later
With the implementation of new intensive care unit (ICU) therapies in the 1970s, multiple organ failure (MOF) emerged as a fulminant inflammatory phenotype leading to early ICU death. Over the…