0000000000949872

AUTHOR

Konstantinos Votis

0000-0001-6381-8326

showing 1 related works from this author

Discovering the Discriminating Power in Patient Test Features Using Visual Analytics: A Case Study in Parkinson’s Disease

2016

Part 11: New Methods and Tools for Big Data Wokshop (MT4BD); International audience; This paper presents a novel methodology for selecting the most representative features for identifying the presence of the Parkinson’s Disease (PD). The proposed methodology is based on interactive visual analytic based on multi-objective optimisation. The implemented tool processes and visualises the information extracted via performing a typical line-tracking test using a tablet device. Such output information includes several modalities, such as position, velocity, dynamics, etc. Preliminary results depict that the implemented visual analytics technique has a very high potential in discriminating the PD …

Visual analytics[ INFO ] Computer Science [cs]Parkinson's diseaseComputer science02 engineering and technology[INFO] Computer Science [cs]Machine learningcomputer.software_genre03 medical and health sciences0302 clinical medicineMulti-objective optimisation0202 electrical engineering electronic engineering information engineeringmedicineFeature (machine learning)[INFO]Computer Science [cs]In patient[SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]Modalitiesbusiness.industryVisual analyticsFeature discrimination powermedicine.diseaseTest (assessment)Power (physics)Identification (information)[ SDV.NEU ] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]Parkinson’s disease[SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]020201 artificial intelligence & image processingData miningArtificial intelligencebusinesscomputer030217 neurology & neurosurgery
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