首页|University of Florence Reports Findings in COVID-19 (Genetic Algorithms for Feat ure Selection in the Classification of COVID-19 Patients)
University of Florence Reports Findings in COVID-19 (Genetic Algorithms for Feat ure Selection in the Classification of COVID-19 Patients)
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2024 OCT 03 (NewsRx)-By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-New research on Coronavirus - COVID-19 is the sub ject of a report. According to news reporting from Florence, Italy, by NewsRx jo urnalists, research stated, "Severe Acute Respiratory Syndrome CoronaVirus-2 (SA RS-CoV-2) infection can cause feared consequences, such as affecting microcircul atory activity. The combined use of HRV analysis, genetic algorithms, and machin e learning classifiers can be helpful in better understanding the characteristic s of microcirculation that are mainly affected by COVID-19 infection." Financial supporters for this research include Regione Toscana, Italy, European Research Council. The news correspondents obtained a quote from the research from the University o f Florence, "This study aimed to verify the presence of microcirculation alterat ions in patients with COVID-19 infection, performing Heart Rate Variability (HRV ) parameters analysis extracted from PhotoPlethysmoGraphy (PPG) signals. The dat aset included 97 subjects divided into two groups: healthy (50 subjects) and pat ients affected by mild-severity COVID-19 (47 subjects). A total of 26 parameters were extracted by the HRV analysis and were investigated using genetic algorith ms with three different subject selection methods and five different machine lea rning classifiers. Three parameters: meanRR, alpha1, and sd2/sd1 were considered significant, combining the results obtained by the genetic algorithm. Finally, machine learning classifications were performed by training classifiers with onl y those three features. The best result was achieved by the binary Decision Tree classifier, achieving accuracy of 82%, specificity (or precision) of 86 %, and sensitivity of 79%."
FlorenceItalyEuropeAlgorithmsCOV ID-19CoronavirusCyborgsEmerging TechnologiesGenetic AlgorithmGenetic A lgorithmsGeneticsMachine LearningMathematicsRNA VirusesRisk and Preven tionSARS-CoV-2Severe Acute Respiratory Syndrome Coronavirus 2ViralVirolo gy
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