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The authors use machine learning to analyze electroencephalogram data and identify slowing patterns that can indicate undetected disorders like epilepsy or dementia

The authors use machine learning and electroencephalogram data to propose a method for improving epilepsy diagnosis.

The authors looked at whether CBD and THC would decrease reproductive rates in a Drosophila melanogaster model. They found that CBD had a greater impact on reducing hatching rates than THC, and that THC resulted in unexpected mortalities.

Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.

Poor air quality is associated with negative effects on human health but can be difficult to measure in an accurate and cost-effective manner. The authors design and test a monitor for measuring indoor air quality using low-cost components.

Here, the authors investigated the role of nonpharmacological interventions in preventing or delaying cognitive impairment in individuals with and without dementia. By using a retrospective case-control study of 22 participants across two senior centers in San Diego, they found no significant differences in self-reported activities. However, they found that their results reflected activity rather than the activity itself, suggesting the need for an alternative type of study.

In this study, the authors investigate associations between use of histamine H₂ receptor antagonists and suicidal ideation in different age groups.

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

The study explores how music and sports impact cognitive development in young children, particularly in relation to learning disorders like ADHD and dyslexia.

Kalirin is a guanine nucleotide exchange factor (GEF) for the GTPase RAC1, linked to schizophrenia and Alzheimer’s Disease. It plays a crucial role in synaptic plasticity by regulating dendritic spine formation and actin cytoskeleton remodeling, which are essential for creating new synapses. Authors developed two novel compounds targeting kalirin, confirming that predictive modeling can indicate biological activity.