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The authors created a 1D model to diagnose hepatomegaly and cirrhosis via ultrasound of the liver.

This study investigated how well food labels from 280 different brands across multiple food and drink categories in India and the US adhered to recommended nutritional labeling standards as outlined by the Codex Alimentarius.

Impact of carbon tax and dividend on financial security

This study compares the performance of two deep learning models, U-Net and DeconvNet, for segmenting gliomas from MRI scans.

Improving the classifier of the difficulty level of Sudoku.

Depression affects millions globally, yet identifying symptoms remains challenging. This study explored detecting depression-related patterns in social media texts using natural language processing and machine learning algorithms, including decision trees and random forests. Our findings suggest that analyzing online text activity can serve as a viable method for screening mental disorders, potentially improving diagnosis accuracy by incorporating both physical and psychological indicators.

Current horticulture practices often rely on pesticides, causing environmental harm. To address this, authors explore the use of ultrasonic sound emissions to detect plant stress at an individual level.

The authors investigated whether the physician-patient relationship affected patient perceptions and treatment adherence.

The authors train a neural network to detect text-based emotions including joy, sadness, anger, fear, love, and surprise.

The authors looked at the ability of Spirulina platensis to reduce contaminants in wastewater in order to develop a more accessible treatment option. They found that S platensis did reduce the concentration of pollutants present within simulated agricultural wastewater.