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Here seeking to develop a method to diagnose, hypertrophic cardiomyopathy which can cause sudden cardiac death, the authors investigated the use of a convolutional neural network (CNN) and long short-term memory (LSTM) models to classify cardiac magnetic resonance and heart electrocardiogram scans. They found that the CNN model had a higher accuracy and precision and better other qualities, suggesting that machine learning models could be valuable tools to assist physicians in the diagnosis of hypertrophic cardiomyopathy.

To address the limitations in predicting the severity of Atrial Septal Defect (ASD), here the authors utilized a fluid-filled chamber model to quantify the relationship between defect size and right atrial fluid output. The findings confirmed that larger ASD diameters result in a linear increase in fluid output, validating a cost-effective model that can improve clinical prognosis and treatment planning for heart failure risks.

The authors combine fine needle aspiration biopsy and machine learning algorithms to develop a breast cancer detection method suitable for resource-constrained regions that lack access to mammograms.

E-cigarettes are often considered a healthier alternative to traditional cigarettes. This team of high school authors investigated the impact of common e-cigarette compounds on C. elegans, and found a number of harmful effects ultimately resulting in injury and neuronal damage.

Pulmonary diseases like lung cancer and valley fever pose serious health challenges, making accurate and rapid diagnostics essential. This study developed a MATLAB-based software tool that uses computer vision techniques to differentiate between these diseases by analyzing features of lung nodules in CT scans, achieving higher precision than traditional methods.

Cardiovascular diseases are the largest cause of death globally, making it a critical area of focus. The circulatory system is required to make the heart function. One component of this system is blood vessels, which is the focus of our study. Our work aims to demonstrate the numeric relationship between a blood vessel's diameter and the number of pumps needed to transport blood.

The misfolding of proteins leads to numerous diseases including Akzheimer’s, Parkinson’s and Type II Diabetes. Understanding of exactly how proteins fold is crucial for many medical advancements. Chenna and Englander addressed this problem by measuring the rate of hydrogen-deuterium exchange within proteins exposed to deuterium oxide in order to further elucidate the process of protein folding. Here, mass spectrometry was used to measure exchange in Cytochrome c and was compared to archived 1H NMR data.

Antibiotics are used to treat dangerous diseases. Over time, however, bacteria are becoming resistant to antibiotics - which poses a threat to humans and animals alike. In this paper, the authors examine how E. coli gains resistance to the antibiotic amoxicillin.

Alcohol is known to cause various developmental diseases including Fetal Alcohol Syndrome. Here the authors investigate the effect of ethanol on the development of zebrafish beta cells, the part of the pancreas associated with Type 1 Diabetes. They find that exposure to ethanol does adversely affect beta-cell development, suggesting that alcohol ingestion during pregnancy may be linked to diabetes in newborns.

Systematic consumption of traditional foods is a popular way of treating diseases in India. Rasam, a soup of spices and tomato with a tamarind base, is a home remedy for viral infections such as the common cold. Here, we investigate if rasam, prepared under household conditions, exhibits antibacterial activity against Escherichia coli and Staphylococcus aureus, two common pathogenic bacteria. Our results show rasam prepared under household conditions lacks antibacterial activity despite its ingredients possessing such properties.