Search results for "DISEASE PREDICTION"

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Suppressiveness of 18 composts against 7 pathosystems : variability in pathogen response

2006

International audience; Compost is often reported as a substrate that is able to suppress soilborne plant pathogens, but suppression varies according to the type of compost and pathosystem. Reports often deal with a single pathogen while in reality crops are attacked by multiple plant pathogens. The goal of the present study was to evaluate the disease suppression ability of a wide range of composts for a range of plant pathogens. This study was conducted by a consortium of researchers from several European countries. Composts originated from different countries and source materials including green and yard waste, straw, bark, biowaste and municipal sewage. Suppressiveness of compost-amende…

0106 biological sciencesRHIZOCTONIA SOLANIpotting mixesPHYTOPHTHORA CINNAMOMIDamping offSoil Sciencecontainer mediaPhytophthora cinnamomi[SDV.SA.SDS]Life Sciences [q-bio]/Agricultural sciences/Soil studyWageningen UR Glastuinbouw01 natural sciencesMicrobiologyRhizoctonia solanidamping-offDISEASE SUPPRESSIVENESSSBiologische bedrijfssystemenFusarium oxysporumwasteVerticillium dahliaepythium-ultimumCOMPOSTFUSARIUM OXYSPORUMBiological Farming Systems2. Zero hungerDISEASE PREDICTIONbiologysoilborne plant-pathogensWageningen UR Greenhouse Horticulturephytophthora-cinnamomiSPATHIPHYLUM CYLINDROCLADIUM04 agricultural and veterinary sciencesPhytophthora nicotianaebiology.organism_classificationPE&RCPotting soilSOILBORNE PLANT PATHOGENSPythium ultimumPHYTOPHTHORA NICOTIANAEAgronomyorganic amendments040103 agronomy & agriculturesoil microbial communities0401 agriculture forestry and fisheriesVERTICILLIUM DAHLIAE010606 plant biology & botanyrhizoctonia-solani
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Effectively Predicting the Presence of Coronary Heart Disease Using Machine Learning Classifiers

2022

Coronary heart disease is one of the major causes of deaths around the globe. Predicating a heart disease is one of the most challenging tasks in the field of clinical data analysis. Machine learning (ML) is useful in diagnostic assistance in terms of decision making and prediction on the basis of the data produced by healthcare sector globally. We have also perceived ML techniques employed in the medical field of disease prediction. In this regard, numerous research studies have been shown on heart disease prediction using an ML classifier. In this paper, we used eleven ML classifiers to identify key features, which improved the predictability of heart disease. To introduce the prediction …

Support Vector MachineHeart DiseasesCoronary DiseaseBiochemistryAtomic and Molecular Physics and OpticsAnalytical ChemistryMachine LearningVDP::Teknologi: 500heart disease dataset; disease prediction; supervised learning; machine learningHumansVDP::Medisinske Fag: 700Neural Networks ComputerElectrical and Electronic EngineeringInstrumentationAlgorithmsSensors; Volume 22; Issue 19; Pages: 7227
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