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Functional Network Connectivity: Possible Biomarker for Autism Spectrum Disorders (ASD)

Wang et al. | Feb 23, 2015

Functional Network Connectivity: Possible Biomarker for Autism Spectrum Disorders (ASD)

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder and is difficult to diagnose in young children. Here magnetoencephalography was used to compare the brain activity in patients with ASD to patients in a control group. The results show that patients with ASD have a high level of activity in different areas of the brain than those in the control group.

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Exploring Political Discourse Among High School Journalists with Web Scraping and AI Technology

Gong et al. | Jun 10, 2025

Exploring Political Discourse Among High School Journalists with Web Scraping and AI Technology

Here the authors provided greater coverage of adolescent stances by investigating the political perspectives and trends of high school journalists, utilizing web scraping methods and artificial intelligence (ChatGPT-4o) to analyze over 153,000 articles. They found that high school publications exhibit lower levels of political polarization compared to mainstream media and that journalists' views, while tending to lean moderately liberal, showed no significant correlation with local voting patterns.

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Machine learning for retinopathy prediction: Unveiling the importance of age and HbA1c with XGBoost

Ramachandran et al. | Sep 05, 2024

Machine learning for retinopathy prediction: Unveiling the importance of age and HbA1c with XGBoost

The purpose of our study was to examine the correlation of glycosylated hemoglobin (HbA1c), blood pressure (BP) readings, and lipid levels with retinopathy. Our main hypothesis was that poor glycemic control, as evident by high HbA1c levels, high blood pressure, and abnormal lipid levels, causes an increased risk of retinopathy. We identified the top two features that were most important to the model as age and HbA1c. This indicates that older patients with poor glycemic control are more likely to show presence of retinopathy.

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Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes

Jalla et al. | Aug 07, 2024

Using Artificial Intelligence to Forecast Continuous Glucose Monitor(CGM) readings for Type One Diabetes
Image credit: The authors

People with Type One diabetes often rely on Continuous Blood Glucose Monitors (CGMs) to track their blood glucose and manage their condition. Researchers are now working to help people with Type One diabetes more easily monitor their health by developing models that will future blood glucose levels based on CGM readings. Jalla and Ghanta tackle this issue by exploring the use of AI models to forecast blood glucose levels with CGM data.

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The effect of joint angle differences on blade velocity in elite and novice saber fencers: A kinematic study

Greene et al. | Mar 02, 2023

 The effect of joint angle differences on blade velocity in elite and novice saber fencers: A kinematic study

Here, recognizing that years of training in saber fencing could expectedly result in optimized movements that result in elite skill levels, the authors used motion tracking and statistical analysis to assess the difference in velocity and blade tip velocity of novice and elite fencers during a vertical blade thrust. They found statistically significant differences in blade tip velocity and elbow joint angle kinematics.

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