The authors use machine learning to analyze electroencephalogram data and identify slowing patterns that can indicate undetected disorders like epilepsy or dementia
Read More...Temporal characterization of electroencephalogram slowing activity types
The authors use machine learning to analyze electroencephalogram data and identify slowing patterns that can indicate undetected disorders like epilepsy or dementia
Read More...Unlocking robotic potential through modern organ segmentation
The authors looked at different models of semantic segmentation to determine which may be best used in the future for segmentation of CT scans to help diagnose certain conditions.
Read More...Monitoring drought using explainable statistical machine learning models
Droughts have a wide range of effects, from ecosystems failing and crops dying, to increased illness and decreased water quality. Drought prediction is important because it can help communities, businesses, and governments plan and prepare for these detrimental effects. This study predicts drought conditions by using predictable weather patterns in machine learning models.
Read More...Sex differences in sleep disorders of Parkinson’s disease patients associated with a genetic risk variant
The authors use known Parkinson's disease-associated genetic variants to compare the prevalence of sleep dysfunction between males and females diagnosed with Parkinson's disease.
Read More...Upward social comparison on standardized test performance in adolescents and adults
The authors test the effect of test score comparison on the self-efficacy of adolescents versus adults.
Read More...Large Language Models are Good Translators
Machine translation remains a challenging area in artificial intelligence, with neural machine translation (NMT) making significant strides over the past decade but still facing hurdles, particularly in translation quality due to the reliance on expensive bilingual training data. This study explores whether large language models (LLMs), like GPT-4, can be effectively adapted for translation tasks and outperform traditional NMT systems.
Read More...Ocean, atmosphere, and cloud quantity on the surface conditions of tidally-locked habitable zone planets
The authors assessed the atmospheric and oceanic parameters necessary for tidally-locked exoplanets to be habitable.
Read More...Using neural networks to detect and categorize sounds
The authors test different machine learning algorithms to remove background noise from audio to help people with hearing loss differentiate between important sounds and distracting noise.
Read More...Modeling stearoyl-coenzyme A desaturase 1 inhibitors to ameliorate α-Syn cytotoxicity in Parkinson's disease
The authors use molecular modeling to test analogs of the stearoyl-coenzyme A desaturase 1 (SCD1) inhibitor MF-438 with implications for future development of Parkinson's disease therapeutics.
Read More...Nature’s reset: The effect of native and invasive plant forage on honey bee nutrition and survival
The authors looked at survival of honey bees over the winter in regards to native and invasive plant availability. They found that native plants provided greater survivability and overall health compared to environments where there was an abundance of invasive plants.
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