Course Name: Precision Care Medicine
Predicting Hospital Readmission Following Acute Kidney Injury
Acute Kidney Injury (AKI) is a sudden loss of renal filtration capacity that leads to toxin and fluid accumulation. Patients...
Subsequence-level approaches for assessing TCR sequences yield insights into T cell repertoire dynamics in ulcerative colitis patients
Ulcerative colitis (UC) is a chronic autoimmune condition characterized by inflammation in the colon and rectum. Though specific etiological factors...
Artificial Intelligence Based Ocular Motor Digital Biomarkers for Neurologic Disease Phenotyping
Neurological disorders impact a large percentage of the global population and are a vast area of research in the clinical...
Genomic Subgrouping of ALS Patients to Investigate Differences in Clinical Progression
Amyotrophic lateral sclerosis (ALS) is a fatal, progressive neurodegenerative disorder marked by significant clinical and genetic heterogeneity, making diagnosis, prognosis,...
Developing Machine Learning Models to Predict for Pediatric Mechanical Ventilation-Associated Events (PedVAE) in Patients
Pediatric ventilator-associated events (PedVAEs) are critical complications in the PICU, linked to increased mortality, prolonged hospital stays, and higher resource...
Decoding Physiological Waveforms for Early Prediction of Sepsis
Sepsis is a life-threatening condition characterized by a dysregulated host response to infection. Early prediction is crucial for improving outcomes...
Deep Learning for Early Prediction of Multi-drug-Resistant Organisms in the Emergency Department
The presence of multidrug resistant organisms (MDROs) and prescribing the appropriate antibiotics to treat them poses a significant challenge in...
Gait Analysis using a High-Resolution Spatiotemporal Pressure Sensing Insole
Gait patterns are valuable biomarkers for neurological conditions. However, instrumented gait analysis (motion capture, force plates) is infeasible outside the...
Comparative Analysis of Standard vs. End-Tidal Carbon Dioxide-Guided Pediatric Cardiopulmonary Resuscitation
This study aims to evaluate the effectiveness of standard cardiopulmonary resuscitation (CPR) guidelines versus end-tidal carbon dioxide (ETCO2)-guided algorithmic CPR...
Early Dynamic Prediction of Organ System Deterioration in ICU Patients
Cardiovascular and respiratory deterioration signify progressive decline in respective organ systems, with cardiovascular (CVS) issues accounting for 17.8% of ICU...
Perioperative Risk Assessment to Predict Hemodynamic Instability in Cardiac Surgery Patients
This project aims to enhance the prediction of hemodynamic instability in cardiac surgery patients undergoing cardiopulmonary bypass, addressing the critical...
Predicting Anti-VEGF Therapy Response in Wet-AMD Patients
In this project, we aim to predict wet age-related macular degeneration patients’ responses to anti-VEGF therapies using machine learning. Wet...
Machine Learning Models to Differentiate the Etiology of Cutaneous Reactions in Post-Stem Cell Transplant Patients
Allogeneic hematopoietic stem cell transplantation (HSCT) is a life-saving treatment for patients with hematologic diseases and is often complicated by...
Deep Learning Detection of Subtle Dynamic Ocular Torsion from Video Ocular Counter Roll (vOCR)
The project focuses on the detection of dynamic ocular torsion from a small dataset of eye video recordings from the...
Monitoring and Prediction of Cardiac Arrest in Pediatric ICU Patients with Machine Learning
Cardiac arrest is a leading cause of mortality within pediatric intensive care units (PICU), causing ~40% of pediatric CA in...
Skin Tone Calibration of Pulse Oximeter Oxygen Saturation Data
Our project aims to enhance the accuracy of pulse oximetry readings across all skin tones to address the critical issue...
Pre-Surgical Risk Stratification using Deep Learning on 12-lead ECGs for Non-Cardiac Populations
Surgical decision-making is critically dependent on accurate assessments of risk, but the effectiveness of electrocardiography (ECG) in evaluating surgical risks...
Resisting Resistance: Using Machine Learning to Optimize Antibiotic Treatment
We are using machine learning to help clinicians decide on whether to broaden the antibiotic spectrum by assessing the risk...
Dynamic Risk Profiling in Patients with Cardiac Inflammatory Syndrome
Development of machine learning models that predict ICU admission for children with Cardiac Inflammatory Syndromes to improve clinical outcomes.
Uncovering Predictors of Neonatal Brain Injury Using Machine Learning
This poster represents the work in Identifying predictors of three patient outcomes of Neonatal Brain Injury using Machine Learning made...
Predicting Successful Weaning Outcomes of Patients on MV Using EHR Data and Physiological Waveforms
Physiological waveforms are used to train a model to predict extubation outcome in order to help physicians predict when to...
Prediction of Mobility After Stroke
Predictive models of mobility recovery and adverse event risk following stroke.
Data-driven Modeling to Improve Pulmonary Hypertension Risk Stratification
Pulmonary hypertension (PH) is characterized by a mean pulmonary arterial (PA) pressure greater than 20 mmHg. The inability of the...
Predicting Liberation from Mechanical Ventilation in the Intensive Care Unit
We aim to develop a model that can accurately predict independence from mechanical ventilation with an end-goal of supporting clinician’s...