Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

Cardiovascular Disease Prediction Modelling: A Machine Learning Approach, Usmaan Al-Shehab, Maduka Gunasinghe, Yousuf Elkhoga, Nimay Patel, Juliana Yang

Rowan-Virtua Research Day

The objective of this project is to utilize the UCI Heart Disease dataset to identify physiological biomarkers that are highly correlated with heart disease incidence. A predictive model can then be developed using these biomarkers to estimate the likelihood of someone having or developing a heart-related condition. This study compares the efficacy of predicting cardiovascular disease as an outcome using three machine learning algorithms: Support Vector Machine, Gaussian Naive Bayes, and logistic regression. Support Vector Machine works by creating hyperplanes between data points to conduct classification. Gaussian Naive Bayes works by using the conditional probabilities of events to classify the …

Inflammatory Marker Levels Among Patients Diagnosed With Autism Spectrum Disorder And Congenital Heart Defects, Patrick Pearce, Venkateswar Venkataraman, Andrea Iannuzzelli, Jennifer Lecomte

Rowan-Virtua Research Day

Autism Spectrum Disorder (ASD) and congenital heart defects (CHD) are conditions that both confer an immense increase in standard of care, and utilization of medical resources addressing comorbidities. One shared symptom that has been consistently cited is inflammation. This review sought to explore the levels of Tumor Necrosis Factor-𝞪 (TNF-𝞪) and Interleukin-6 (IL-6) between patients diagnosed as having either ASD or CHD. By compiling published data containing the mean values of these two inflammatory markers within these populations, it was shown that while both have significantly elevated levels compared to a phenotypically normal demographic, there is no significant difference between …

Serological Proteomic Screening And Evaluation Of A Recombinant Egg Antigen For The Diagnosis Of Low-Intensity Schistosoma Mansoni Infections In Endemic Area In Brazil, Vanessa Silva-Moraes, Lisa Marie Shollenberger, William Castro-Borges, Ana Lucia Teles Rabello, Donald A. Harn, Lia Carolina Soares Medeiros, Wander De Jesus Jeremias, Liliane Maria Vidal Siqueira, Caroline Stephane Salviano Pereira, Maria Luysa Camargos Pedrosa, Nathalie Bonatti Franco Almeida, Aureo Almeida, Jose Roberto Lambertucci, Nidia Francisca De Figueiredo Carneiro, Paulo Marcos Zech Coelho, Refaella Fortini Queiroz Grenfell

Biological Sciences Faculty Publications

Background

Despite decades of use of control programs, schistosomiasis remains a global public health problem. To further reduce prevalence and intensity of infection, or to achieve the goal of elimination in low-endemic areas, there needs to be better diagnostic tools to detect low-intensity infections in low-endemic areas in Brazil. The rationale for development of new diagnostic tools is that the current standard test Kato-Katz (KK) is not sensitive enough to detect low-intensity infections in low-endemic areas. In order to develop new diagnostic tools, we employed a proteomics approach to identify biomarkers associated with schistosome-specific immune responses in hopes of developing …

Biomarkers Of Sepsis: A Retrospective Approach, Jose M. Roberts

Williams Honors College, Honors Research Projects

Background: Biomarkers are taking the spotlight in becoming the norm for early diagnoses. Sepsis is an inflammatory disease that increases metabolic rate in children. The first biomarker is hyponatremia. Hyponatremia is a frequent electrolyte imbalance in clinical practice, often observed in children with inflammatory disease and infection. Presence of hyponatremia is associated with electrical signaling imbalances, inflammation and renal dysfunction. The clinical value of hyponatremia in pediatric patients is unknown. The C-reactive protein is a second biomarker. Its presence signifies that necrotic cells and inflammation are present.

Objectives: To evaluate the use of biomarkers in children seen in the Emergency …