Browse Articles

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.

The authors assess the relationship between supportive family environments and internalized stigma in adolescents.

The authors looked at the impact of vitamin A (retinol) on growth of S. epidermidis (most abundant bacterium on the skin) and E. coli (found in the gut microbiome, but not on the skin).

This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.

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.

This paper utilizes multiple publicly available cancer datasets to explore the abundance of different genetic dependencies across various cancer types. They explore this by looking at four genes highly associated with cancer and their genetic and pathogenic relationships.

The authors looked at using computer vision to evaluate the degree of exotropia in individuals with strabismus.

The authors developed a quantum inspired model for stock market fluctuations.

Analysis of the Sloan green and red photometry of the Type Ia supernova 2024neh

Athletes with performance anxiety may struggle to play their best and enjoy the game. Various factors may impact how much anxiety an athlete feels, including how much experience they have in the sport. Concha-Ortiz and Navins survey teenage club volleyball players to look for relationships between years of experience and performance anxiety symptoms.