Modeling Nanoparticle-Based Therapy in Tumor Growth

By: Hailey V.Year: 2023School: Portola HighGrade: 10Science Teacher: Erica Borquez In the realm of medical science, the landscape of cancer therapy has been undergoing a remarkable transformation over the past decade. The emergence of targeted therapies has opened new avenues to interrupt the intricate molecular processes that fuel the growth of cancer cells. With each patient’s cancer being

Monitoring Health for the Elderly Using Machine Learning Anomaly Detection

By: Mark M.Year: 2022School: Rancho San Joaquin MiddleGrade: 8Science Teacher: Paige Morris This project provides a novel and personalized solution for monitoring dehydration in the elderly. Four Machine Learning algorithms were compared to determine which one best detected anomalies in the timings of an elderly subject’s nightly bathroom visits, such as long gaps between visits

New Brain Computer Interfaces for Neurologically Impaired Subjects Augmented with Gaming Technology to Improve Cognitive functions in ADHD Subjects

By: Nithin P.Year: 2021School: Northwood HighGrade: 11Science Teacher: Jane Yoon Amyotrophic lateral sclerosis (ALS), a progressive neuromuscular degenerative disease, restricts patients’ communication capacity a few years after onset resulting in a severe degradation in their quality of life. ALS patients currently have a means to communicate through non-invasive brain-computer interfaces (BCI). This research adapts and

Determining Electrical Resistivity of Cartilage

By: Patrick N.Year: 2021School: Sage HillGrade: 11Science Teacher: Derek Shapiro Determining the electrical resistivity of articular cartilage in humans is important for assessing its biomechanical function and physiology. Many methods of measuring electrical resistivity in biological organisms are invasive and harmful to their components. Other approaches to studying these properties have not been cost-effective nor

Exploring novel techniques to predict liver fibrosis in patients with non-alcoholic fatty liver disease

By: Devon C.Year: 2021School: Arnold O. Beckman HighGrade: 9Science Teacher: Philip Chow In this study, Devon aimed to demonstrate that machine learning (ML) can be used as an effective tool to help predict non-alcoholic fatty liver disease (NAFLD) associated liver fibrosis (LF). Materials and Methods: Multiple ML models were trained and tested, including logistic regression

Variation in Gene Expression Reveals Genes Predictive of Overall Survival in the Triple-Negative Breast Cancer Subtype.

By: Nitin S.Year: 2021School: Troy HighGrade: 12Science Teacher: James Kirkpatrick Abstract: Breast cancer (BC) subtypes are categorized by their molecular subtype as ER+, PR+, or HER2+. Cancers that lack expression of these receptors are the highly heterogeneous and deadly triple-negative (TN). Thus, there is an urgency to identify targeted therapies for TN patients. In this

Herbivory In Humans

By: Akshata T.Year: 2020School: Aliso Niguel High School, 9th gradeDivision: Senior Humans today eat a variety of foods, including both meats and veggies. They think of themselves as omnivorous creatures, or both meat and plant eaters. On the other hand, some people choose to be vegetarians, sticking to a diet of only plant-based foods. I