Archivio Istituzionale della RicercaCardiovascularandneurologicaldiseasesincludingtheirinteractionsaregettingtheattentionofresearchersandphysicians.Bothdiseasesoftensharecommonbiomarkers,riskfactors,andbiological pathways.Bynow,researchershaveconfirmedthatproblemsrelatedtocardiovascularleadtoneurologicalbadoutcomesandviceversa. Inaddition,researchershavestartedtousemachine/deeplearning algorithmsforbetterdiagnosis.Bynow,fewexamplesarepublishedonlittledatasetsconsistingofcomputedtomographyimages,electrocardiograms,electroencephalograms,andsoon,butmostofthework isnotdonebyartificialintelligence(AI).Inthiswork,wereviewedanumberofstudiesthathaveeither usedAIormanualcomputationwithconventionaltechniquesondifferentimagingmodalities.Fromall studies,itisfoundthatimagingmodalitiescansupportphysiciansinbetterdiagnosisofneurological outcomesfollowingcardiaceventsand/ordiseasesandviceversa.Moreover,AIdriventechnologies, like machinelearninganddeeplearning,couldbeusefultodelineateaccuratemodelsofdiseasesrelatedto neuro-cardiacpathologiesforpredictionsofconsequentbadoutcomesrelatedtothedifferentstages
Medical imaging and artificial intelligence to investigate neuro-cardiac pathologies and discover hidden relationships – a state of the art review / Shah, Syed Taimoor Hussain; Calati, Veronika; Bizzarri, Alessandra; Deriu, Marco Agostino. - ELETTRONICO. - (2022). (Intervento presentato al convegno Neurodevelopmental Impairments in Preterm Children - Computational Advancements (DETERMINED 2022)) [10.5281/zenodo.8009881].
Medical imaging and artificial intelligence to investigate neuro-cardiac pathologies and discover hidden relationships – a state of the art review
Shah, Syed Taimoor Hussain;Bizzarri, Alessandra;Deriu, Marco Agostino
2022
Abstract
Cardiovascularandneurologicaldiseasesincludingtheirinteractionsaregettingtheattentionofresearchersandphysicians.Bothdiseasesoftensharecommonbiomarkers,riskfactors,andbiological pathways.Bynow,researchershaveconfirmedthatproblemsrelatedtocardiovascularleadtoneurologicalbadoutcomesandviceversa. Inaddition,researchershavestartedtousemachine/deeplearning algorithmsforbetterdiagnosis.Bynow,fewexamplesarepublishedonlittledatasetsconsistingofcomputedtomographyimages,electrocardiograms,electroencephalograms,andsoon,butmostofthework isnotdonebyartificialintelligence(AI).Inthiswork,wereviewedanumberofstudiesthathaveeither usedAIormanualcomputationwithconventionaltechniquesondifferentimagingmodalities.Fromall studies,itisfoundthatimagingmodalitiescansupportphysiciansinbetterdiagnosisofneurological outcomesfollowingcardiaceventsand/ordiseasesandviceversa.Moreover,AIdriventechnologies, like machinelearninganddeeplearning,couldbeusefultodelineateaccuratemodelsofdiseasesrelatedto neuro-cardiacpathologiesforpredictionsofconsequentbadoutcomesrelatedtothedifferentstages
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https://hdl.handle.net/11583/2984360