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Due to a critical shortage of donor hearts, researchers are exploring cardiac xenotransplantation—transplanting animal hearts into humans—as a potential solution. This study synthesized nearly two decades of preclinical research to evaluate multiple factors affecting xenograft survival.

The authors looked how different working conditions impacted the microbiome of the human skin.

The authors looked at the ability of different deep learning models to predict the presence of lung cancer from chest CT scans. They found that a pre-trained CNN model performed better than an autoencoder model.

There is a need for safe and effective therapies to prevent platelet aggregation associated with cardiovascular diseases. Prabhakar and Prabhakar test to see whether dietary supplements claiming to reduce cardiovascular disease risk will affect aggregation of human platelets.

The global issue of water quality has led to the use of machine learning models, like ANN and SVM, to predict water potability. However, these models can be complex and resource-intensive. This research aimed to find a simpler, more efficient model for water quality prediction.

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.

Here the authors investigated air quality forecasting in India, comparing traditional time series models like SARIMA with deep learning models like LSTM. The research found that SARIMA models, which capture seasonal variations, outperform LSTM models in predicting Air Quality Index (AQI) levels across multiple Indian cities, supporting the hypothesis that simpler models can be more effective for this specific task.

Here the authors sought to investigate whether and how cerebral stroke and other health-related variables are influenced together and amongst each other by using statistical analyses. Their analysis suggested relations between nearly all variables considered, with the strongest association between having heart disease and a cerebral stroke.

This article helps in understanding the effect of various social determinants on maternal mortality in the United States. It explains the relationship between maternal mortality rates and factors like race, income, education, and health insurance access.

The authors develop a method for detecting fake AI-generated images from real images.