首页|Research from University of Rhode Island Has Provided New Data on Machine Learni ng (Analysis of Emerging Variants of Turkey Reovirus using Machine Learning)
Research from University of Rhode Island Has Provided New Data on Machine Learni ng (Analysis of Emerging Variants of Turkey Reovirus using Machine Learning)
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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on artificial in telligence have been published. According to news originating from the Universit y of Rhode Island by NewsRx editors, the research stated, “Avian reoviruses cont inue to cause disease in turkeys with varied pathogenicity and tissue tropism. T urkey enteric reovirus has been identified as a causative agent of enteritis or inapparent infections in turkeys.” Our news editors obtained a quote from the research from University of Rhode Isl and: “The new emerging variants of turkey reovirus, tentatively named turkey art hritis reovirus (TARV) and turkey hepatitis reovirus (THRV), are linked to tenos ynovitis/arthritis and hepatitis, respectively. Turkey arthritis and hepatitis r eoviruses are causing significant economic losses to the turkey industry. These infections can lead to poor weight gain, uneven growth, poor feed conversion, in creased morbidity and mortality and reduced marketability of commercial turkeys. To combat these issues, detecting and classifying the types of reoviruses in tu rkey populations is essential. This research aims to employ clustering methods, specifically K-means and Hierarchical clustering, to differentiate three types o f turkey reoviruses and identify novel emerging variants. Additionally, it focus es on classifying variants of turkey reoviruses by leveraging various machine le arning algorithms such as Support Vector Machines, Naive Bayes, Random Forest, D ecision Tree, and deep learning algorithms, including convolutional neural netwo rks (CNNs). The experiments use real turkey reovirus sequence data, allowing for robust analysis and evaluation of the proposed methods.”
University of Rhode IslandCyborgsEme rging TechnologiesMachine Learning
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