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publications (hide)25
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1Methods used in the development of common data models for health data: Scoping review
N. Ahmadi, M. Zoch, P. Kelbert, R. Noll, J. Schaaf, M. Wolfien, and M. Sedlmayr. JMIR Med. Inform., (August 2023)
2 months ago by @scadsfct
show all tags
Observational
Data
Healthcare;
Interoperability;
health
Repositories;
Interoperability
Partnership
elements;
elements
Healthcare
model;
;
Process;
Medical
Informatics;
data;
harmonisation;
Suggestive
data
Process
record;
stakeholder
Standardized
Repositories
Outcomes
Partnership;
involvement
common
record
Development
harmonisation
model
Informatics
electronic
ObservationalDataHealthcare;Interoperability;healthRepositories;InteroperabilityPartnershipelements;elementsHealthcaremodel;;Process;MedicalInformatics;data;harmonisation;SuggestivedataProcessrecord;stakeholderStandardizedRepositoriesOutcomesPartnership;involvementcommonrecordDevelopmentharmonisationmodelInformaticselectronic
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1Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis
A. Akshay, M. Katoch, N. Shekarchizadeh, M. Abedi, A. Sharma, F. Burkhard, R. Adam, K. Monastyrskaya, and A. Gheinani. Gigascience, (January 2024)
2 months ago by @scadsfct
show all tags
problems;
visualization
learning;
data
machine
analysis;
AutoML;
classification
problems;visualizationlearning;datamachineanalysis;AutoML;classification
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1Multi-source dataset of e-commerce products with attributes for property matching
D. Ayala, I. Hernández, D. Ruiz, and E. Rahm. Data Brief, 41 (107884): 107884 (April 2022)
2 months ago by @scadsfct
show all tags
integration;
engineering;
Data
Ontology;
Property
matching
integration;engineering;DataOntology;Propertymatching
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2Breaking Barriers: Workshop on Open Data Practices in AutoUI Research
P. Ebel, P. Bazilinskyy, A. Hwang, W. Ju, H. Sandhaus, A. Srinivasan, Q. Yang, and P. Wintersberger. Adjunct Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, page 227--230. (2023)
7 days ago by @scads.ai
show all tags
AutoUI
Data
Research
Workshop
from:scadsfct
Open
Practices
AutoUIDataResearchWorkshopfrom:scadsfctOpenPractices
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2Breaking Barriers: Workshop on Open Data Practices in AutoUI Research
P. Ebel, P. Bazilinskyy, A. Hwang, W. Ju, H. Sandhaus, A. Srinivasan, Q. Yang, and P. Wintersberger. Adjunct Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, page 227--230. (2023)
7 days ago by @scadsfct
show all tags
AutoUI
Data
Research
Workshop
Open
Practices
AutoUIDataResearchWorkshopOpenPractices
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2Destination Prediction Based on Partial Trajectory Data
P. Ebel, I. Göl, C. Lingenfelder, and A. Vogelsang. (2020)
9 days ago by @scadsfct
show all tags
Destination
Partial
Prediction
Data
Trajectory
Based
on
DestinationPartialPredictionDataTrajectoryBasedon
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2Destination Prediction Based on Partial Trajectory Data
P. Ebel, I. Göl, C. Lingenfelder, and A. Vogelsang. (2020)
9 days ago by @scads.ai
show all tags
Destination
Partial
Prediction
Data
Trajectory
from:scadsfct
Based
on
DestinationPartialPredictionDataTrajectoryfrom:scadsfctBasedon
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2ICEBOAT: An Interactive User Behavior Analysis Tool for Automotive User Interfaces
P. Ebel, K. Gülle, C. Lingenfelder, and A. Vogelsang. Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, New York, NY, USA, Association for Computing Machinery, (2022)
9 days ago by @scadsfct
show all tags
Design
Interaction
Visualization
Driving
Tools
Data
In-Vehicle
Naturalistic
Information
Human-Computer
System
DesignInteractionVisualizationDrivingToolsDataIn-VehicleNaturalisticInformationHuman-ComputerSystem
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2Exploring Millions of User Interactions with ICEBOAT: Big Data Analytics for Automotive User Interfaces
P. Ebel, K. Gülle, C. Lingenfelder, and A. Vogelsang. Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, page 81--92. (2023)
7 days ago by @scads.ai
show all tags
User
Interfaces
Data
Interactions
from:scadsfct
ICEBOAT
Analytics
Big
Automotive
UserInterfacesDataInteractionsfrom:scadsfctICEBOATAnalyticsBigAutomotive
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2ICEBOAT: An Interactive User Behavior Analysis Tool for Automotive User Interfaces
P. Ebel, K. Gülle, C. Lingenfelder, and A. Vogelsang. Adjunct Proceedings of the 35th Annual ACM Symposium on User Interface Software and Technology, New York, NY, USA, Association for Computing Machinery, (2022)
9 days ago by @scads.ai
show all tags
Design
Interaction
Visualization
Driving
Tools
Data
In-Vehicle
from:scadsfct
Naturalistic
Information
Human-Computer
System
DesignInteractionVisualizationDrivingToolsDataIn-Vehiclefrom:scadsfctNaturalisticInformationHuman-ComputerSystem
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2Exploring Millions of User Interactions with ICEBOAT: Big Data Analytics for Automotive User Interfaces
P. Ebel, K. Gülle, C. Lingenfelder, and A. Vogelsang. Proceedings of the 15th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, page 81--92. (2023)
7 days ago by @scadsfct
show all tags
User
Interfaces
Data
Interactions
ICEBOAT
Analytics
Big
Automotive
UserInterfacesDataInteractionsICEBOATAnalyticsBigAutomotive
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1Toward Veracity Assessment in RDF Knowledge Bases: An Exploratory Analysis
D. Esteves, A. Rula, A. Reddy, and J. Lehmann. J. Data and Information Quality, (February 2018)
2 months ago by @scadsfct
show all tags
exploratory
trustworthiness,
benchmark,
fact
DeFacto,
data
checking,
quality,
analysis
data,
linked
exploratorytrustworthiness,benchmark,factDeFacto,datachecking,quality,analysisdata,linked
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1A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters
J. Gerritzen, A. Hornig, B. Gröger, and M. Gude. Journal of Composites Science, 6 (10): 318 (2022)
7 days ago by @scadsfct
show all tags
Shear
Driven
Composites
Experimental
Data
Dependent
Thermoplastic
Strain
3D
Approach
Characterisation
Rate
Fibre
Modelling
Deformation
Failure
Reinforced
ShearDrivenCompositesExperimentalDataDependentThermoplasticStrain3DApproachCharacterisationRateFibreModellingDeformationFailureReinforced
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1Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology
K. Hoffmann, K. Cazemier, C. Baldow, S. Schuster, Y. Kheifetz, S. Schirm, M. Horn, T. Ernst, C. Volgmann, C. Thiede and 7 other author(s). BMC Med. Inform. Decis. Mak., 20 (1): 28 (February 2020)
2 months ago by @scadsfct
show all tags
decision-making;
workflow;
Haematology;
Support
Mathematical
therapy
Clinical
Data
Routine
treatment
management;
simulation;
modelling;
system
optimization;
Individual
Computer
planning;
Model-based
decision-making;workflow;Haematology;SupportMathematicaltherapyClinicalDataRoutinetreatmentmanagement;simulation;modelling;systemoptimization;IndividualComputerplanning;Model-based
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2Mathematical principles of topological and geometric data analysis
P. Joharinad, and J. Jost. Springer International Publishing, Cham, (2023)
9 days ago by @scads.ai
show all tags
data
geometric
from:scadsfct
analysis
topological
datageometricfrom:scadsfctanalysistopological
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1Automated algorithm selection: Survey and perspectives
P. Kerschke, H. Hoos, F. Neumann, and H. Trautmann. Evol. Comput., 27 (1): 3--45 (2019)
2 months ago by @scadsfct
show all tags
feature-based
learning;
metalearning
data
analysis;
optimisation;
automated
streams.;
exploratory
combinatorial
continuous
machine
approaches;
Automated
selection;
algorithm
configuration;
landscape
feature-basedlearning;metalearningdataanalysis;optimisation;automatedstreams.;exploratorycombinatorialcontinuousmachineapproaches;Automatedselection;algorithmconfiguration;landscape
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2PEARL: Physical Environment based Augmented Reality Lenses for In-Situ Human Movement Analysis
W. Luo, Z. Yu, R. Rzayev, M. Satkowski, S. Gumhold, M. McGinity, and R. Dachselt. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 381, New York, NY, USA, Association for Computing Machinery, (April 2023)
9 days ago by @scads.ai
show all tags
visualization
reality
data
augmented/mixed
from:scadsfct
analysis
Analytics
In-situ
affordance
Immersive
referents
movement
physical
visualizationrealitydataaugmented/mixedfrom:scadsfctanalysisAnalyticsIn-situaffordanceImmersivereferentsmovementphysical
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2PEARL: Physical Environment based Augmented Reality Lenses for In-Situ Human Movement Analysis
W. Luo, Z. Yu, R. Rzayev, M. Satkowski, S. Gumhold, M. McGinity, and R. Dachselt. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 381, New York, NY, USA, Association for Computing Machinery, (April 2023)
9 days ago by @scadsfct
show all tags
visualization
reality
data
augmented/mixed
analysis
Analytics
In-situ
affordance
Immersive
referents
movement
physical
visualizationrealitydataaugmented/mixedanalysisAnalyticsIn-situaffordanceImmersivereferentsmovementphysical
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1Stability selection enables robust learning of partial differential equations from limited noisy data
S. Maddu, B. Cheeseman, I. Sbalzarini, and C. Müller. (2019)
a month ago by @scadsfct
show all tags
(physics.data-an),
Analysis,
Probability
Data
sciences,
Numerical
Statistics
FOS:
Machine
Physical
sciences
Analysis
(cs.LG),
Learning
(math.NA),
Mathematics,
and
Computer
information
(physics.data-an),Analysis,ProbabilityDatasciences,NumericalStatisticsFOS:MachinePhysicalsciencesAnalysis(cs.LG),Learning(math.NA),Mathematics,andComputerinformation
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1Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction
D. Nam, J. Chapiro, V. Paradis, T. Seraphin, and J. Kather. JHEP Rep., 4 (4): 100443 (April 2022)
2 months ago by @scadsfct
show all tags
a
disease;
HCC,
or
intelligence;
liver
multivariable
non-alcoholic
multimodal
ML,
artificial
WSIs,
images;
prediction
support
integration
TACE,
DICOM,
AI,
network;
deep
neural
Digital
Diagnosis;
MVI,
transarterial
fatty
microvascular
convolutional
in
learning;
imaging;
Communications
invasion;
NAFLD,
chemoembolisation;
hepatocellular
Reporting
steatohepatitis;
Transparent
Individual
slide
machine
Prognosis
Artificial
data
for
NASH,
whole
Medicine;
TRIPOD,
of
CNN,
and
Imaging
carcinoma;
diagnostic
system;
model
adisease;HCC,orintelligence;livermultivariablenon-alcoholicmultimodalML,artificialWSIs,images;predictionsupportintegrationTACE,DICOM,AI,network;deepneuralDigitalDiagnosis;MVI,transarterialfattymicrovascularconvolutionalinlearning;imaging;Communicationsinvasion;NAFLD,chemoembolisation;hepatocellularReportingsteatohepatitis;TransparentIndividualslidemachinePrognosisArtificialdataforNASH,wholeMedicine;TRIPOD,ofCNN,andImagingcarcinoma;diagnosticsystem;model
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publications (hide)25
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1Methods used in the development of common data models for health data: Scoping review

1Machine Learning Made Easy (MLme): a comprehensive toolkit for machine learning-driven data analysis

1Multi-source dataset of e-commerce products with attributes for property matching

2Breaking Barriers: Workshop on Open Data Practices in AutoUI Research

2Breaking Barriers: Workshop on Open Data Practices in AutoUI Research

2Destination Prediction Based on Partial Trajectory Data

2Destination Prediction Based on Partial Trajectory Data

2ICEBOAT: An Interactive User Behavior Analysis Tool for Automotive User Interfaces

2Exploring Millions of User Interactions with ICEBOAT: Big Data Analytics for Automotive User Interfaces

2ICEBOAT: An Interactive User Behavior Analysis Tool for Automotive User Interfaces

2Exploring Millions of User Interactions with ICEBOAT: Big Data Analytics for Automotive User Interfaces

1Toward Veracity Assessment in RDF Knowledge Bases: An Exploratory Analysis

1A Data Driven Modelling Approach for the Strain Rate Dependent 3D Shear Deformation and Failure of Thermoplastic Fibre Reinforced Composites: Experimental Characterisation and Deriving Modelling Parameters

1Integration of mathematical model predictions into routine workflows to support clinical decision making in haematology

2Mathematical principles of topological and geometric data analysis

1Automated algorithm selection: Survey and perspectives

2PEARL: Physical Environment based Augmented Reality Lenses for In-Situ Human Movement Analysis

2PEARL: Physical Environment based Augmented Reality Lenses for In-Situ Human Movement Analysis

1Stability selection enables robust learning of partial differential equations from limited noisy data

1Artificial intelligence in liver diseases: Improving diagnostics, prognostics and response prediction

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