Stress and anxiety have become more prevalent issues in recent years with teenagers especially at risk. Recent studies show that experiencing stress while learning can impair brain-cell communication thus negatively impacting learning. Green tea is believed to have the opposite effect, aiding in learning and memory retention. In this study, the authors used Lymnaea stagnalis , a pond snail, to explore the relationship between green tea and a stressor that impairs memory formation to determine the effects of both green tea and stress on the snails’ ability to learn, form, and retain memories. Using a conditioned taste aversion (CTA) assay, where snails are exposed to a sweet substance followed by a bitter taste with the number of biting responses being recorded, the authors found that stress was shown to be harmful to snail learning and memory for short-term, intermediate, and long-term memory.
Read More...Browse Articles
Transfer Learning for Small and Different Datasets: Fine-Tuning A Pre-Trained Model Affects Performance
In this study, the authors seek to improve a machine learning algorithm used for image classification: identifying male and female images. In addition to fine-tuning the classification model, they investigate how accuracy is affected by their changes (an important task when developing and updating algorithms). To determine accuracy, a set of images is used to train the model and then a separate set of images is used for validation. They found that the validation accuracy was close to the training accuracy. This study contributes to the expanding areas of machine learning and its applications to image identification.
Read More...Machine Learning Algorithm Using Logistic Regression and an Artificial Neural Network (ANN) for Early Stage Detection of Parkinson’s Disease
Despite the prevalence of PD, diagnosing PD is expensive, requires specialized testing, and is often inaccurate. Moreover, diagnosis is often made late in the disease course when treatments are less effective. Using existing voice data from patients with PD and healthy controls, the authors created and trained two different algorithms: one using logistic regression and another employing an artificial neural network (ANN).
Read More...The Effects of Confinement on the Associative Learning of Gallus gallus domesticus
This study aimed to determine if confinement affects associative learning in chickens. The research found that the difference in time lapsed before chickens began to consume cottage cheese before and after confinement was significant. These results suggest that confinement distresses chickens, as it impairs associative learning without inducing confusion.
Read More...Using machine learning to understand social media discourse on the co-use of tobacco and cannabis
The authors used developed a machine learning tool for studying social media discourse surrounding use of tobacco and cannabis.
Read More...The effects of image manipulation on classification of cervical spondylosis X-ray images using deep learning
Drought prediction in the Midwestern United States using deep learning
The authors studied the ability of deep learning models to predict droughts in the midwestern United States.
Read More...Impact of length of audio on music classification with deep learning
The authors looked at how the length of an audio clip used of a song impacted the ability to properly classify it by musical genre.
Read More...Explainable AI tools provide meaningful insight into rationale for prediction in machine learning models
The authors compare current machine learning algorithms with a new Explainable AI algorithm that produces a human-comprehensible decision tree alongside predictions.
Read More...Applying machine learning to breast cancer diagnosis: A high school student’s exploration using R
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.
Read More...