![Evaluating the clinical applicability of neural networks for meningioma tumor segmentation on 3D MRI](/rails/active_storage/representations/proxy/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaHBBaWdSIiwiZXhwIjpudWxsLCJwdXIiOiJibG9iX2lkIn19--bb1a6945148f009dcc7ac61140a1b60b0b13b869/eyJfcmFpbHMiOnsibWVzc2FnZSI6IkJBaDdCem9MWm05eWJXRjBTU0lJY0c1bkJqb0dSVlE2QzNKbGMybDZaVWtpRFRZd01IZzJNREErQmpzR1ZBPT0iLCJleHAiOm51bGwsInB1ciI6InZhcmlhdGlvbiJ9fQ==--33b2b080106a274a4ca568f8742d366d42f20c14/Figure-6-Sreedhar-JEI-23-265_R2.png)
Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.
Read More...Evaluating the clinical applicability of neural networks for meningioma tumor segmentation on 3D MRI
Authors emphasize the challenges of manual tumor segmentation and the potential of deep learning models to enhance accuracy by automatically analyzing MRI scans.
Read More...Quantitative analysis and development of alopecia areata classification frameworks
This article discusses Alopecia areata, an autoimmune disorder causing sudden hair loss due to the immune system mistakenly attacking hair follicles. The article introduces the use of deep learning (DL) techniques, particularly convolutional neural networks (CNN), for classifying images of healthy and alopecia-affected hair. The study presents a comparative analysis of newly optimized CNN models with existing ones, trained on datasets containing images of healthy and alopecia-affected hair. The Inception-Resnet-v2 model emerged as the most effective for classifying Alopecia Areata.
Read More...Effects of material advantage and space advantage on the Komodo and Stockfish chess engines
Chess engines, or computer programs built to play chess, outperform even the best human players. Kaushikan and Park investigate the inner workings of these chess engines by studying popular chess engines' evaluations of which side of a chess match is most likely to win, and how this is affected by the number of pieces and controlled squares on each side.
Read More...Evaluating the effectiveness of machine learning models for detecting AI-generated art
The authors investigate how well AI-detection machine learning models can detect real versus AI-generated art across different art styles.
Read More...Model selection and optimization for poverty prediction on household data from Cambodia
Here the authors sought to use three machine learning models to predict poverty levels in Cambodia based on available household data. They found teat multilayer perceptron outperformed the other models, with an accuracy of 87 %. They suggest that data-driven approaches such as these could be used more effectively target and alleviate poverty.
Read More...Administration of Stephania tetrandra to Drosophila melanogaster to create obsessive compulsive disorder model
In this study the authors looked at the extract of Stephania tetrandra and its impact on symptoms related to obsessive compulsive disorder in fruit flies.
Read More...A chemical and overwintering honey bee apiary field study comparing new and expired amitraz miticide
In this study, the authors test the longevity of a anti-mite compound, amitraz, in commercially-sold strips and the age-dependent efficacy of these strips in preventing honey bee colony collapse by ectoparasitic mite Varroa destructor.
Read More...The Potential of Fibroblast Growth Factors to Stimulate Hair Growth In Vitro
Identifying treatments that can stimulate hair growth use could help those struggling with undesirable hair loss. Here, the authors show that Fibroblast Growth Factors can stimulate the division of cells isolated from the mouse hair follicle. Their results suggest that this family of growth factors might be helpful in stimulating hair growth in living animals as well.
Read More...The Parent-Child Relationship During the College Planning Process
To explore the parent-child relationship during college planning, authors surveyed high school juniors from two private schools (boarding school vs. non-boarding parochial school). After coding, survey answers indicate students at boarding schools were found to have greater fear of parental control and disappointment, while students at non-boarding parochial schoolexpressed a greater need for parental assistance.
Read More...The Effects of Post-Consumer Waste Polystyrene on the Rate of Mealworm Consumption
In a world where plastic waste accumulation is threatening both land and sea life, Green et al. investigate the ability of mealworms to breakdown polystyrene, a non-recyclable form of petrochemical-based polymer we use in our daily lives. They confirm that these organisms, can degrade various forms of polystyrene, even after it has been put to use in our daily lives. Although the efficiency of the degradation process still requires improvement, the good news is, the worms are tiny and themselves are biodegradable, so we can use plenty of them without worrying about space and how to get rid of them. This is very promising and certainly good news for the planet.
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