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Breast cancer mammographic screening by different guidelines among women of different races/ethnicities

Wang et al. | Aug 27, 2023

Breast cancer mammographic screening by different guidelines among women of different races/ethnicities

Mammographic screening is a common diagnostic tool for breast cancer among average-risk women. The authors hypothesized that adherence rates for mammographic screening may be lower among minorities (non-Hispanic black (NHB) and Hispanic/Latino) than among non-Hispanic whites (NHW) regardless of the guideline applied. The findings support other studies’ results that different racial/ethnic and socio-demographic factors can affect screening adherence. Therefore, healthcare providers should promote breast cancer screening especially among NHW/Hispanic women and women lacking insurance coverage.

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A Retrospective Study of Research Data on End Stage Renal Disease

Ponnaluri et al. | Mar 09, 2016

A Retrospective Study of Research Data on End Stage Renal Disease

End Stage Renal Disease (ESRD) is a growing health concern in the United States. The authors of this study present a study of ESRD incidence over a 32-year period, providing an in-depth look at the contributions of age, race, gender, and underlying medical factors to this disease.

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Using explainable artificial intelligence to identify patient-specific breast cancer subtypes

Suresh et al. | Jan 12, 2024

Using explainable artificial intelligence to identify patient-specific breast cancer subtypes

Breast cancer is the most common cancer in women, with approximately 300,000 diagnosed with breast cancer in 2023. It ranks second in cancer-related deaths for women, after lung cancer with nearly 50,000 deaths. Scientists have identified important genetic mutations in genes like BRCA1 and BRCA2 that lead to the development of breast cancer, but previous studies were limited as they focused on specific populations. To overcome limitations, diverse populations and powerful statistical methods like genome-wide association studies and whole-genome sequencing are needed. Explainable artificial intelligence (XAI) can be used in oncology and breast cancer research to overcome these limitations of specificity as it can analyze datasets of diagnosed patients by providing interpretable explanations for identified patterns and predictions. This project aims to achieve technological and medicinal goals by using advanced algorithms to identify breast cancer subtypes for faster diagnoses. Multiple methods were utilized to develop an efficient algorithm. We hypothesized that an XAI approach would be best as it can assign scores to genes, specifically with a 90% success rate. To test that, we ran multiple trials utilizing XAI methods through the identification of class-specific and patient-specific key genes. We found that the study demonstrated a pipeline that combines multiple XAI techniques to identify potential biomarker genes for breast cancer with a 95% success rate.

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Time-Efficient and Low-Cost Neural Network to detect plant disease on leaves and reduce food loss and waste

Singh et al. | Apr 24, 2023

Time-Efficient and Low-Cost Neural Network to detect plant disease on leaves and reduce food loss and waste

About 25% of the food grown never reaches consumers due to spoilage, and 11.5 billion pounds of produce from gardens are wasted every year. Current solutions involve farmers manually looking for and treating diseased crops. These methods of tending crops are neither time-efficient nor feasible. I used a convolutional neural network to identify signs of plant disease on leaves for garden owners and farmers.

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Simulations of Cheetah Roaming Demonstrate the Effect of Safety Corridors on Genetic Diversity and Human-Cheetah Conflict

Acton et al. | Apr 02, 2018

Simulations of Cheetah Roaming Demonstrate the Effect of Safety Corridors on Genetic Diversity and Human-Cheetah Conflict

Ecological corridors are geographic features designated to allow the movement of wildlife populations between habitats that have been fragmented by human landscapes. Corridors can be a pivotal aspect in wildlife conservation because they preserve a suitable habitat for isolated populations to live and intermingle. Here, two students simulate the effect of introducing a safety corridor for cheetahs, based on real tracking data on cheetahs in Namibia.

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The sweetened actualities of neural membrane proteins: A computational structural analysis

Chauhan et al. | Nov 03, 2022

The sweetened actualities of neural membrane proteins: A computational structural analysis

Here, seeking to better understand the roles of glycans in the receptors of active sites of neuronal cells, the authors used molecular dynamics simulations to to uncover the dynamic nature of N-glycans on membrane proteins. The authors suggest the study of theinteractions of these membrane poreins could provide future potential therapeutic targets to treat mental diseases.

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Sri Lankan Americans’ views on U.S. racial issues are influenced by pre-migrant ethnic prejudice and identity

Gunawardena et al. | Apr 18, 2022

Sri Lankan Americans’ views on U.S. racial issues are influenced by pre-migrant ethnic prejudice and identity

In this study, the authors examined how Sri Lankan Americans (SLAs) view racial issues in the U.S. The main hypothesis is that SLAs, as a minority in the U.S., are supportive of the Black Lives Matter movement and its political goal, challenging the common notion that SLAs are anti-Black. The study found that a majority of SLAs believe the U.S. has systemic racism, favor BLM, and favor affirmative action. IT also found that Tamil SLAs have more favorable views of BLM and affirmative action than Sinhalese SLAs.

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