Reexamining The Croton Aqueduct: A Ward-Level Microhistorical Analysis Of Infrastructure And Cholera Mortality In 1849 New York City,
2026
CUNY Graduate Center
Reexamining The Croton Aqueduct: A Ward-Level Microhistorical Analysis Of Infrastructure And Cholera Mortality In 1849 New York City, Alexandria R. Toothman
Dissertations, Theses, and Capstone Projects
This work reexamines the Croton Aqueduct’s role in public health by shifting analysis from the citywide level to the ward level, revealing that infrastructure expansion did not produce uniform benefits across New York City. When the Croton Aqueduct opened in 1842, it was celebrated as an achievement that would deliver pure water and eliminate disease. However, only seven years after its opening, in 1849, cholera returned with greater force in the Sixth Ward. This work shows that the uneven distribution of Croton infrastructure corresponded with uneven cholera mortality rates, challenging narratives that present Croton as a singular triumph of urban …
Evaluation Of The Effectiveness Of Antihypertensive Therapy Chosen Through Maternal Hemodynamic Profile Analysis,
2026
University of South Alabama
Evaluation Of The Effectiveness Of Antihypertensive Therapy Chosen Through Maternal Hemodynamic Profile Analysis, Margaret Weimer
Poster Presentations
In treatment of emergent hypertension, the American College of Obstetricians and Gynecologists (ACOG) recommends both oral labetalol and nifedipine, with no preference shown between the two. These medications have different mechanisms of action. Studies have suggested that consideration of hemodynamic profile may be an effective way to determine medication, but have not considered the Rule of 55, a simple calculation to predict hemodynamic profile.
Goals: 1. Determine if tailoring the antihypertensive to patient’s hemodynamic profile is associated with better control of blood pressure. 2. Determine if the Rule of 55 is an accurate method to determine hemodynamic profile.
Comparative Machine Learning Models For Disease Risk Prediction,
2026
Marshall University
Comparative Machine Learning Models For Disease Risk Prediction, Mercy Mawusi Agbley
Theses, Dissertations and Capstones
Accurate prediction of disease outcomes is crucial for improving clinical decision-making and enabling early intervention. This study compares the performance of various statistical and machine learning models for clinical risk prediction using two healthcare datasets: diabetic retinopathy and heart disease. The models assessed include Logistic Regression, LASSO, k-Nearest Neighbors (KNN), Support Vector Machines (SVM), Neural Networks, Random Forests, Gradient Boosting Machines (GBM), and a stacked ensemble model. Prior to modeling, datasets were split into train and test sets. Standardization was applied to numeric features whilst categorical features were one-hot encoded. These transformations were later applied to the test set. Principal …
Investigating The Connection Between Als Through The Mutation R522s In The Rna Binding Protein,
2026
University of North Alabama
Investigating The Connection Between Als Through The Mutation R522s In The Rna Binding Protein, Dennia Estrella-Vargas, Lydia Uptain
Mathematics
Amyotrophic lateral sclerosis (ALS) is a fatal disease that causes the deterioration of motor neurons , death is usually due to respiratory paralysis. The variant R522S was chosen because it is near a hot spot of pathogenic variants. It is an arginine-to-serine swap, this swap is present in pathogenic variants near the 522 position, such as R514S, R521S, R524S. Recent evidence suggests that arginine-deficiency can influence disease progression.
Differential Impact Of Admission Type And Clinical Complexity On Diabetes Hospitalization Costs Among African American And Hispanic Patients In Southeastern Virginia,
2026
Macon & Joan Brock Virginia Health Sciences at Old Dominion University
Differential Impact Of Admission Type And Clinical Complexity On Diabetes Hospitalization Costs Among African American And Hispanic Patients In Southeastern Virginia, Ismail El Moudden, Asra Amidi, Reem Sharaf-Alddin, Michael C. Bittner, Qi Zhang
Department of Obstetrics & Gynecology Faculty Publications
Background
Diabetes mellitus (DM) imposes substantial healthcare costs with documented disparities among African Americans and Hispanic patients. To inform care delivery and resource allocation, this study identified hospitalization cost predictors among African American and Hispanic patients with diabetes in Southeastern Virginia.
Methods
We analyzed 6,011 hospital discharges from the Virginia Health Information database (2016-2020) for adults aged 18-85 with diabetes. Discharges were classified by Medicare Severity Diagnosis-Related Groups: DM with complications/comorbidities (DCC, n = 3,328), DM with major complications/comorbidities (DMCC, n = 1,518), and DM without major complications/comorbidities (DWO, n = 1,165). Because cost distributions were right-skewed (skewness 3.5-8.24), we …
A Comparative Study Of Classification Methods For Healthcare Analytics,
2026
University of North Florida
A Comparative Study Of Classification Methods For Healthcare Analytics, Xueting Zhao
UNF Graduate Theses and Dissertations
This thesis presents a comparative study of logistic regression, Linear Discriminant Analy- sis (LDA), and Quadratic Discriminant Analysis (QDA) for binary classification in healthcare analytics, integrating theoretical derivation, simulation, and real-data application. A facto- rial simulation study crosses the covariance structure (equal vs. unequal), predictor correla- tion (ρ ∈ {0, 0.5, 0.9}), dimensionality (p ∈ {2, 5, 10}) and sample size (n ∈ {50, 100, 200}) across 54 scenarios with 1,000 Monte Carlo replicates each. Three main findings emerge. Logistic regression and LDA are nearly interchangeable when the assumption of equal-covariance holds. QDA achieves substantially better discrimi- nation when class-specific …
Explainable Ai For Liver Transplant Survival Prediction: Integrating Immunological Mismatch Features,
2025
Bowling Green State University
Explainable Ai For Liver Transplant Survival Prediction: Integrating Immunological Mismatch Features, Sourab Shaik
Honors Projects
Liver Transplantations are crucial treatment for end-stage liver disease. However, a persistent deficit of donor organs necessitates maximizing the utility of each available graft to minimize failure rates. We evaluated whether donor–recipient molecular immunogenicity metrics - Electrostatic and Hydrophobic Mismatch Scores (HMS/EMS) and eplet-based counts - improve post–liver-transplant survival prediction. The analytic cohort comprised adult, first time, single-organ deceased-donor transplants drawn from Scientific Registry of Transplant Recipients; follow-up was truncated at five years, and the endpoint was all-cause graft failure (earliest of graft failure or death; otherwise, censored). HLA variables were derived via high- resolution conversion and molecular mismatch computations …
Association Of Estimated Plasma Volume Status With Invasive Hemodynamics And Adverse Clinical Outcomes In Patients With Pulmonary Hypertension And Chronic Kidney Disease,
2025
Thomas Jefferson University
Association Of Estimated Plasma Volume Status With Invasive Hemodynamics And Adverse Clinical Outcomes In Patients With Pulmonary Hypertension And Chronic Kidney Disease, Andrew Geller, Jose Manuel Martinez Manzano, Esteban Kosak Lopez, Phuuwadith Wattanachayakul, John Malin, Raul Leguizamon, Tara John, Rasha Khan, Ian Mclaren, Alexander Prendergast, Simone Jarrett, Kevin Bryan Lo, Christian Witzke
Einstein Health Papers
Identifying noninvasive measures to assess intravascular volume status and risk stratify patients with pulmonary hypertension (PH) and chronic kidney disease (CKD) is needed. We assessed the predictive value of estimated plasma volume status (ePVS) using the Strauss-derived Duarte formula in PH-CKD patients. This single-center retrospective cohort analysis included patients with PH and CKD Stage 3b (CKD3b), Stage 4 (CKD4), or Stage 5 (CKD5) who underwent right heart catheterization from 2018 to 2023. Patients were categorized into low ePVS (< 6.2) and high ePVS (≥ 6.2) using Youden's J statistics. We used the Cox-proportional hazards model, adjusting for age, sex, and body mass index, to investigate the association between …
Breast Cancer Survival Rates And Determinants In Ethiopia: A Systematic Review And Meta-Analysis Of Longitudinal Studies,
2025
Thomas Jefferson University
Breast Cancer Survival Rates And Determinants In Ethiopia: A Systematic Review And Meta-Analysis Of Longitudinal Studies, Abenezer M. Tafese, Meseker T. Fentie, Beminate L. Seifu, Angwach A. Asnake, Bikiltu D. Dirbaba, Abdisa G. Jara, Elsabeth Tizazu Asare, Brandon George
College of Population Health Faculty Papers
BACKGROUND: Breast cancer is the most common cancer and the leading cause of cancer mortality among women in Ethiopia, accounting for 32% of new cancer cases and 17.6% of cancer deaths. Despite its growing burden, comprehensive data on survival rates and contributing factors remain limited. This systematic review and meta-analysis aimed to synthesize existing data on breast cancer survival in Ethiopia and identify key determinants influencing outcomes.
METHODS: A comprehensive systematic search was conducted in PubMed, Web of Science, Scopus, Embase, and CINAHL to identify studies on breast cancer survival in Ethiopia published between January 2014 and August 2024. Eligible …
Sequential Data Modeling Of Influenza A Via Traditional, Dwt-Gpr Hybrid, And Deep Learning Architectures,
2025
The University of Texas Rio Grande Valley
Sequential Data Modeling Of Influenza A Via Traditional, Dwt-Gpr Hybrid, And Deep Learning Architectures, Edmund Fosu Agyemang
Theses and Dissertations
Influenza A is responsible for 290,000 to 650,000 respiratory deaths a year, though this estimate is an improvement from years past due to improved sanitation, healthcare practices, and vaccination programs. In this study, we perform a comparative analysis of traditional, deep-learning and discrete wavelet (DWT)-Gaussian Process (GP) hybrid models to predict Influenza A outbreaks. Using historical data from January 2009 to December 2023, we compared the performance of traditional ARIMA and ETS models, four variants of DWT-GPR models and six distinct deep learning architectures: Simple RNN, LSTM, GRU, BiLSTM, BiGRU and Transformer. The results reveal a clear superiority of all …
Analysis Of Errors In The Management Of Cutaneous Disorders,
2025
Macon & Joan Brock Virginia Health Sciences at Old Dominion University
Analysis Of Errors In The Management Of Cutaneous Disorders, Robert J. Pariser, Sarah Alnaif
Department Dermatology Faculty Publications
In this study, we prospectively and retrospectively evaluated the occurrence of errors in the management of cutaneous disorders from patient visits and medical records in a single dermatology practice in southeast Virginia over a 3-year period (June 2020-July 2023). Providers should be able to improve diagnostic accuracy by utilizing established rapid bedside diagnostic techniques.
Machine Learning Models Leveraging Patient-Similarity And Clinical Temporality For Disease Prognoses,
2025
University of Thi Qar
Machine Learning Models Leveraging Patient-Similarity And Clinical Temporality For Disease Prognoses, Ahmad F. Al Musawi
Theses and Dissertations
Electronic Health Records (EHRs) constitute a comprehensive and high-dimensional repository of clinical data, encompassing a wide array of patient-level information such as diagnoses, procedures, medications, laboratory results, and unstructured clinical narratives. These data hold immense potential for advancing predictive modeling in healthcare, including tasks such as disease progression modeling, hospital readmission prediction, and length of stay (LoS) estimation. However, the intrinsic complexity of EHR data—manifested in its heterogeneity, sparsity, and temporal dynamics—poses significant analytical challenges that limit the generalizability and interpretability of conventional machine learning models. Recent methodological advancements in deep learning and graph-based learning, particularly Graph Neural Networks (GNNs), …
Pediatric Cancer Incidence, Temporal Trends, And Mortality In The United States By Health Disparities Indicators, Seer (1973-2014),
2025
Macon & Joan Brock Virginia Health Sciences at Old Dominion University
Pediatric Cancer Incidence, Temporal Trends, And Mortality In The United States By Health Disparities Indicators, Seer (1973-2014), Prachi P. Chavan, Laurens Holmes Jr.
Epidemiology, Biostatistics, & Environmental Health Faculty Publications
Background: Pediatric cancer incidence has been increasing in the United States, despite improvement in pediatric cancer survival. This steady increase in incidence trends is not completely understood but maybe associated with social and environmental factors. In this study we aimed to assess the cumulative incidence, temporal trends, and mortality rates in pediatric cancer. Additionally, we examined sub-group variability in both incidence and mortality rates. Methods: Data from Surveillance, Epidemiology, and End Results (SEER) −18 from 1973–2014 were used for the purpose of analysis in this study. Age-adjusted incidence rates were used to assess temporal trends in cancer among children aged < 1–19 years. Univariable and multivariable binomial regression models were used to examine the association between race and cancer mortality while adjusting for potential confounders. Results: There were 92,594 cancer diagnoses during this period. White children comprised 74,758, (80.7%), black children 10,030, (10.8%), and other races 6648, (7.2%). Overall the age-adjusted cumulative incidence was slightly higher among white children (16.4%) than black children (12.4%) and other (13.0%). Children aged 15–19 years and those in metropolitan regions were more likely to be diagnosed with pediatric cancer. Relative to females, males were 16% more likely to die from the disease [adjusted Risk Ratio (aRR): 1.16, 95% Confidence Interval (CI): 1.09–1.22]. Additionally, compared to white children, black children had higher mortality rates [(aRR): 1.37, 99% CI: 1.23–1.52]. Conclusions: There is an increasing trend in pediatric cancer incidence; while white children have the highest incidence, black children and males indicated a survival disadvantage, indicative of racial and sex variability in overall pediatric cancer in the United States.
Effect Of Universal Health Coverage On Neonatal Mortality Rate In Sub-Saharan Africa: Addressing Missing Data In Health Indicators,
2025
Northern Illinois University
Effect Of Universal Health Coverage On Neonatal Mortality Rate In Sub-Saharan Africa: Addressing Missing Data In Health Indicators, Elizabeth Nalule Arihoona
Graduate Research Theses & Dissertations
This study utilizes two mixed-effects models to examine the effect of Universal Health Coverage on Neonatal Mortality Rate (NMR) in 30 countries of Sub-Saharan Africa from 2000-2019 while addressing the missing data in health indicators. Using natural cubic spline interpolation, I impute the missing values in the health coverage indices to preserve the location- specific trends of the data. Findings indicate that among the health Coverage indices, only Index1, which directly relates to coverage of maternal, newborn and child health services is significantly associated with reduced NMR. While higher Current Health Expenditure is associated with reduced NMR, a higher share …
Third Ward Casper 2023 Final Report,
2024
Texas Southern University
Third Ward Casper 2023 Final Report, Zuri Dale, Vishnu Nepal, Debra Maxwell, Ashlee Young
COVID Research
The 2023 Third Ward CASPER Final Report conducted by Texas Southern University (TSU) and the Houston Health Department assessed public health conditions in Houston's Third Ward community. The initiative utilized the Community Assessment for Public Health Emergency Response (CASPER) methodology to gather household-based data, informing public health decisions, emergency responses, and future resource allocation.
Objective and Key Findings: The mission aimed to assess health needs, promote health resources, and build community relationships. Notable findings include that over 36% of households reported hypertension, while 19% experienced poor mental health. Access barriers to healthcare persisted, particularly due to lack of insurance. Nearly …
Exploring The Diagnostic Potential Of Radiomics-Based Pet Image Analysis For T-Stage Tumor Diagnosis,
2024
East Tennessee State University
Exploring The Diagnostic Potential Of Radiomics-Based Pet Image Analysis For T-Stage Tumor Diagnosis, Victor Aderanti
Electronic Theses and Dissertations
Cancer is a leading cause of death globally, and early detection is crucial for better
outcomes. This research aims to improve Region Of Interest (ROI) segmentation
and feature extraction in medical image analysis using Radiomics techniques
with 3D Slicer, Pyradiomics, and Python. Dimension reduction methods, including
PCA, K-means, t-SNE, ISOMAP, and Hierarchical Clustering, were applied to highdimensional features to enhance interpretability and efficiency. The study assessed the ability of the reduced feature set to predict T-staging, an essential component of the TNM system for cancer diagnosis. Multinomial logistic regression models were developed and evaluated using MSE, AIC, BIC, and Deviance …
An Application Of An In-Depth Advanced Statistical Analysis In Exploring The Dynamics Of Depression, Sleep Deprivation, And Self-Esteem,
2024
East Tennessee State University
An Application Of An In-Depth Advanced Statistical Analysis In Exploring The Dynamics Of Depression, Sleep Deprivation, And Self-Esteem, Muslihat Gaffari
Electronic Theses and Dissertations
Depression, intertwined with sleep deprivation and self-esteem, presents a significant challenge to mental health worldwide. The research shown in this paper employs advanced statistical methodologies to unravel the complex interactions among these factors. Through log-linear homogeneous association, multinomial logistic regression, and generalized linear models, the study scrutinizes large datasets to uncover nuanced patterns and relationships. By elucidating how depression, sleep disturbances, and self-esteem intersect, the research aims to deepen understanding of mental health phenomena. The study clarifies the relationship between these variables and explores reasons for prioritizing depression research. It evaluates how statistical models, such as log-linear, multinomial logistic regression, …
Gender-Specific Mental Health Outcomes In Central America: A Natural Experiment,
2024
Ursinus College
Gender-Specific Mental Health Outcomes In Central America: A Natural Experiment, Thea Nagasuru
Computer Science Summer Fellows
While COVID lockdown measures have had varying effects on the mental health of different demographics, several bodies of research have noted their disparate effect on women. Why is women's mental health more negatively impacted by lockdown measures, and how much more are they impacted than men? How can we predict and mitigate these negative effects on women? This paper aims to contribute to answering those questions by comparing COVID stringency measures and their effect on the gap in depression rates between men and women in two neighboring countries: Nicaragua and Honduras.
Accessible Real-Time Eye-Gaze Tracking For Neurocognitive Health Assessments, A Multimodal Web-Based Approach,
2024
California Polytechnic State University, San Luis Obispo
Accessible Real-Time Eye-Gaze Tracking For Neurocognitive Health Assessments, A Multimodal Web-Based Approach, Daniel C. Tisdale
Master's Theses
We introduce a novel integration of real-time, predictive eye-gaze tracking models into a multimodal dialogue system tailored for remote health assessments. This system is designed to be highly accessible requiring only a conventional webcam for video input along with minimal cursor interaction and utilizes engaging gaze-based tasks that can be performed directly in a web browser. We have crafted dynamic subsystems that capture high-quality data efficiently and maintain quality through instances of user attrition and incomplete calls. Additionally, these subsystems are designed with the foresight to allow for future re-analysis using improved predictive models, as well as enable the creation …
Health And Healthcare: Designing For The Social Determinants Of Health And Blue Zones In North Nashville,
2024
Belmont University
Health And Healthcare: Designing For The Social Determinants Of Health And Blue Zones In North Nashville, Rebecca Tonguis, Honor Thomas, Olivia Hobbs
[Archive] Belmont University Research Symposium (BURS)
Owned by North Nashville’s First Community Church, a now empty site in the Osage-North Fisk neighborhood of North Nashville has been identified as a potential site for a new location of The Store, in addition to a community-centric architectural development based on the social determinants of health and informed by the principles behind Blue Zones, the locations with the highest lifespans in the world. Opened by Brad Paisley and Kimberly Williams-Paisley, The Store is a free grocery store that “allow[s] people to shop for their basic needs in a way that protects dignity and fosters hope”, for which North Nashville …
