
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...A natural language processing approach to skill identification in the job market
The authors looked at using machine learning to identify skills needed to apply for certain jobs, specifically looking at different techniques to parse apart the text. They found that Bidirectional Encoder Representation of Transforms (BERT) performed best.
Read More...SmartZoo: A Deep Learning Framework for an IoT Platform in Animal Care
Zoos offer educational and scientific advantages but face high maintenance costs and challenges in animal care due to diverse species' habits. Challenges include tracking animals, detecting illnesses, and creating suitable habitats. We developed a deep learning framework called SmartZoo to address these issues and enable efficient animal monitoring, condition alerts, and data aggregation. We discovered that the data generated by our model is closer to real data than random data, and we were able to demonstrate that the model excels at generating data that resembles real-world data.
Read More...The precision of machine learning models at classifying autism spectrum disorder in adults
Autism spectrum disorder (ASD) is hard to correctly diagnose due to the very subjective nature of diagnosing it: behavior analysis. Due to this issue, we sought to find a machine learning-based method that diagnoses ASD without behavior analysis or helps reduce misdiagnosis.
Read More...High school students’ attitudes towards diverse cultures and ethnicities
The authors looked at how a student's own background influence their attitude towards integration of diverse cultures and ethnicities. While overall students viewed other groups positively, the authors found that groups still indicated they felt judged by their peers.
Read More...Inhibitory effects of captan on growth of Escherichia coli and Bacillus coagulans
The authors test the effects of the pesticide captan on the growth of gut microbiome bacteria including Bacillus coagulan and Escherichia coli.
Read More...Artificial intelligence assisted violin performance learning
In this study the authors looked at the ability of artificial intelligence to detect tempo, rhythm, and intonation of a piece played on violin. Technology such as this would allow for students to practice and get feedback without the need of a teacher.
Read More...The effects of UV-C and ionizing radiation on the functions of Escherichia Coli
In this study, the authors send E. coli cultures to space via the Cubes in SpaceTM program to determine if ultraviolet C and ionizing radiation negatively affect bacterial growth.
Read More...Heavy Metal Contamination of Hand-Pressed Well Water in HuNan, China
Unprocessed water from hand-pressed wells is still commonly used as a source of drinking water in Chenzhou, the “Nonferrous Metal Village” of China. Long et al. conducted a study to measure the heavy metal contamination levels and potential health effects in this area. Water samples were analyzed through Inductively Coupled Plasma Optical Emission Spectroscopy (ICPOES) and the concentrations of 20 metal elements. Results showed that although none of the samples had dangerous levels of heavy metals, the concentrations of Al, Fe, and Mn in many locations substantially exceeded those suggested in the Chinese Drinking Water Standard and the maximum contaminant levels of Environmental Protection Agency (EPA). The authors have made an important discovery regarding the water safety in HuNan and their suggestions to install water treatment systems would greatly benefit the community.
Read More...A comparative analysis of machine learning approaches to predict brain tumors using MRI
The authors use machine learning on MRI images of brain tissue to predict tumor onset as an avenue for early detection of brain cancer.
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