Scientific Reports (2025).
Abstract We applied Growth Mixture Modeling (GMM) to characterize county-level COVID-19 incidence rate (IR) trajectories across three distinct waves in the United States from March 15 to November 2, 2020. GMM enabled the identification of latent subpopulations with shared temporal patterns of disease spread, offering a flexible analytic framework for uncovering both known and evolving disparities. Across the three periods, up to five trajectory groups were identified, revealing substantial geographic and temporal heterogeneity.
Journal of Bone & Joint Surgery (2025).
Abstract Background: Total knee arthroplasty (TKA) is among the most commonly performed elective procedures. Tourniquet use remains debated regarding patient outcomes and postoperative experience. Methods: Within the PEPPER trial framework, 5,684 primary TKAs were analyzed; 4,866 (85.6%) used a tourniquet and 818 (14.4%) did not. Primary outcomes were KOOS‑JR, PROMIS‑PH10, and numeric pain rating, collected preoperatively and at 1, 3, and 6 months. Secondary outcomes included length of stay, discharge disposition, analgesic consumption, and complications.
Critical Care Explorations (2025).
Abstract IMPORTANCE: In patients with traumatic brain injury (TBI), baseline pupillary assessment is routine; however, the occurrence rate and clinical significance of pupil abnormalities over the early course of hospitalization remain poorly characterized. OBJECTIVES: To determine whether the occurrence and frequency of pupil abnormalities within the first 72 hours of ICU admission are associated with unfavorable discharge outcomes and to assess whether incorporating this frequency improves the performance of an established prognostic model.
Scientific Reports (2025).
Abstract Space occupying cerebral edema is a feared complication after large ischemic stroke, occurring in up to 30% of patients with middle cerebral artery (MCA) occlusion and peaking 2–4 days after injury. Little is known about the factors and outcomes associated with peak edema timing, especially after 96 h. We aimed to characterize differences and compare discharge status between patients who experienced maximum midline shift (MLS) or decompressive hemicraniectomy (DHC) in the acute (< 48 h), average (48–96 h), and subacute (> 96 h) groups.
Annals of Neurology (2025).
Abstract Objective: This study assesses whether longitudinal quantitative pupillometry predicts neurological deterioration after large middle cerebral artery (MCA) stroke and determines how early changes are detectable. Methods: This prospective, single‑center observational cohort study included patients with large MCA stroke admitted to Boston Medical Center’s intensive care unit (2019–2024). Associations between time‑to‑neurologic deterioration and quantitative pupillometry, including Neurological Pupil Index (NPi), were assessed using Cox proportional hazards models with time‑dependent covariates adjusted for age, sex, and Alberta Stroke Program Early CT Score.
Statistics and Data Science in Imaging (2024).
Abstract Recent advances in medical imaging technologies have led to the proliferation of multimodal quantitative imaging data in cancer. Quantitative medical imaging data—numerical representations derived from radiology and pathology—enable precise characterization of tumor biology to assess progression, therapy response, and prognosis. However, analytical challenges arise due to high dimensionality, structural correlations, and heterogeneity. This review summarizes state‑of‑the‑art statistical methods for quantitative imaging—including topological, functional, and shape analyses; spatial process models; and modern ML—highlighting clinical applications in oncology and open problems for future research.
Scientific Reports (2024).
Abstract Individual-level assessment of health and well-being permits analysis of community well-being and health risk evaluations across several dimensions of health. It also enables comparison and rankings of reported health and well-being for large geographical areas such as states, metropolitan areas, and counties. However, there is large variation in reported well-being within such large spatial units underscoring the importance of analyzing well-being at more granular levels, such as ZIP codes.
Annals of Applied Statistics (2023).
Abstract Volumetric imaging features are used in cancer research to determine the size and the composition of a tumor and have been shown to be prognostic of overall survival. In this paper we focus on the analysis of tumor component proportions of brain cancer patients collected through The Cancer Genome Atlas (TCGA) project. Our main goal is to identify pathways and corresponding genes that can explain the heterogeneity of the composition of a brain tumor.
Medical Image Analysis (2023).
Abstract: We propose a statistical framework to analyze radiological magnetic resonance imaging (MRI) and genomic data to identify the underlying radiogenomic associations in lower grade gliomas (LGG). We devise a novel imaging phenotype by dividing the tumor region into concentric spherical layers that mimics the tumor evolution process. MRI data within each layer is represented by voxel–intensity-based probability density functions which capture the complete information about tumor heterogeneity.
iScience (2023).
Abstract Quantifying the risk of progression to Alzheimer’s disease (AD) could help identify persons who could benefit from early interventions. We used data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n = 544, discovery) and the National Alzheimer’s Coordinating Center (NACC, n = 508, validation), subdividing individuals with mild cognitive impairment (MCI) into risk groups based on CSF amyloid‑β and identifying differential gray‑matter patterns. We created neural‑network–survival models trained on non‑parcellated T1‑weighted MRIs to predict MCI→AD conversion (integrated Brier score: 0.