The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.
Read More...A comparative analysis of machine learning approaches to predict brain tumors using MRI
The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.
Read More...An explainable model for content moderation
The authors looked at the ability of machine learning algorithms to interpret language given their increasing use in moderating content on social media. Using an explainable model they were able to achieve 81% accuracy in detecting fake vs. real news based on language of posts alone.
Read More...Predicting asthma-related emergency department visits and hospitalizations with machine learning techniques
Seeking to investigate the effects of ambient pollutants on human respiratory health, here the authors used machine learning to examine asthma in Lost Angeles County, an area with substantial pollution. By using machine learning models and classification techniques, the authors identified that nitrogen dioxide and ozone levels were significantly correlated with asthma hospitalizations. Based on an identified seasonal surge in asthma hospitalizations, the authors suggest future directions to improve machine learning modeling to investigate these relationships.
Read More...Observing effects of resolving leaky gut on sugar, fat, and insulin levels during type 1 diabetes in fruit flies
This study uses a fruit fly model of type 1 diabetes (T1D) to determine whether strengthening intestinal tight junctions to reduce intestinal permeability would improve T1D symptoms.
Read More...Citrate and lactate drive glioblastoma progression via activation of tumor-associated macrophages
The authors looked at the impact of citrate and lactate on glioblastoma progression. Their results provide important insights for future immunotherapies aimed at treating glioblastoma.
Read More...Locating sources of a high energy cosmic ray extensive air shower using HiSPARC data
Using the data provided by the University of Twente High School Project on Astrophysics Research with Cosmics (HiSPARC), an analysis of locations for possible high-energy cosmic ray air showers was conducted. An example includes an analysis conducted of the high-energy rain shower recorded in January 2014 and the use of Stellariumâ„¢ to discern its location.
Read More...Giving Teens a Voice: Sources of Stress for High School Students
The authors investigate the negative effects stress has on teen mental and physical health. Through a survey, they give Virginia teens a voice in revising the Health and Physical Education curriculum to include a standards of learning (SOL). Notably they identify factors contributing to stress levels including homework level, amount of free and sleep time, parental pressure and family encouragement.
Read More...CDK7 inhibition disrupts androgen signaling and induces metabolic rewiring in prostate cancer cells
The authors used RNA-seq datasets to assess the effect of CDK7 inhibition on transcriptional pathways in castration-resistant prostate cancer cells.
Read More...Gender differences in social media, sleep, and cognition in U.S. teens
The authors survey teenagers within the United States regarding the effect of social media use on sleep quality and attention span.
Read More...An assessment of controllable etiological factors involved in neonatal seizure using a Monte Carlo model
The authors used Monte Carlo simulations to assess the impacts of various factors on neonatal seizure risk.
Read More...