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The authors studied the accuracy of two commonly used explainable AI techniques for detecting pneumonia in chest x-rays.

When granular materials are poured onto a surface, they form conical piles whose slopes increase before reaching a stable angle of repose. We found that this angle evolution follows a previously unrecognized two-phase exponential growth pattern that is conserved across granular materials with diverse particle properties. The parameters of this model correlate with particle friction and are influenced by deposition conditions, providing a quantitative framework for describing pile formation.

This manuscript explores the performance of five different machine learning models in classifying brain tumors from a dataset of MRI scans. The authors find that several of the models showed >90% accuracy. Thus, the authors suggest that machine learning models demonstrate potential for effective implementation in clinical settings, including as a diagnostic tool that can be used to complement the expertise of neuroradiologists.

This study examined how social determinants of health (SDH) relate to vision loss by analyzing publicly available data from 18 northern and southern U.S. states and using Bayesian correlation analysis.

Crohn’s disease is a chronic inflammatory bowel condition with symptoms like abdominal pain, fatigue, diarrhea, and malnutrition. Though there's no cure, various treatments help manage it. This study explored the potential impact of Massa Medicata Fermentata (MMF), a fermented Chinese herbal medicine containing Saccharomyces cerevisiae, on Crohn’s disease.

Investigation of the potential of waxworm saliva, the secretion of Galleria mellonella, for plastic degradation.

The authors looked at the ability to use audio clips to analyze the progression of Parkinson's disease.

Predicting antibody structures and antibody-antigen complexes using AlphaFold

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.

Utilization of neural network to analyze Free Word Association to predict accurately age, gender, first language, and current country.