UB Paderborn / Katalog / Suche / in CDI

Changes in prognosis of the Danish multiple sclerosis population over time

Multiple sclerosis, 2022-12, Vol.28 (14), p.2190-2201

2022

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A GP-based ensemble classification framework for time-changing streams of intrusion detection data

Soft computing (Berlin, Germany), 2020-12, Vol.24 (23), p.17541-17560

2020

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AI-Empowered Process Mining for Complex Application Scenarios: Survey and Discussion

Journal on data semantics, 2021-06, Vol.10 (1-2), p.77-106

2021

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Correction to: AI-Empowered Process Mining for Complex Application Scenarios: Survey and Discussion

Journal on data semantics, 2021, Vol.10 (3-4), p.409-409

2021

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Socioeconomic status of the elderly MS population compared to the general population: a nationwide Danish matched cross-sectional study

Frontiers in neurology, 2023-06, Vol.14, p.1214897-1214897

2023

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Comparative transcriptomics reveals the conserved building blocks involved in parallel evolution of diverse phenotypic traits in ants

Genome Biology, 2016-03, Vol.17 (1), p.43-43, Article 43

2016

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Ant colonies prefer infected over uninfected nest sites

PloS one, 2014-11, Vol.9 (11), p.e111961-e111961

2014

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The impact of healthcare systems on the clinical diagnosis and disease-modifying treatment usage in relapse-onset multiple sclerosis: a real-world perspective in five registries across Europe

Therapeutic advances in neurological disorders, 2023-01, Vol.16, p.17562864231198963-17562864231198963

2023

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Proportion and characteristics of secondary progressive multiple sclerosis in five European registries using objective classifiers

Multiple sclerosis journal - experimental, translational and clinical, 2023-01, Vol.9 (1), p.20552173231153557-20552173231153557

2023

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An ensemble-based approach to the security-oriented classification of low-level log traces

Expert systems with applications, 2020-09, Vol.153, p.113386, Article 113386

2020

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Process Mining meets argumentation: Explainable interpretations of low-level event logs via abstract argumentation

Information systems (Oxford), 2022-07, Vol.107, p.101987, Article 101987

2022

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Pushing More AI Capabilities into Process Mining to Better Deal with Low-Quality Logs

Business Process Management Workshops, p.5-11

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Data- & compute-efficient deviance mining via active learning and fast ensembles

Journal of intelligent information systems, 2024-01

2024

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Corrigendum to “Process mining meets argumentation: Explainable interpretations of low-level event logs via abstract argumentation” [Inform. Syst. 107 (2022) 101987]

Information systems (Oxford), 2022-12, Vol.110, p.102103, Article 102103

2022

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COVID‐19 vaccination and relapse activity: A nationwide cohort study of patients with multiple sclerosis in Denmark

European journal of neurology, 2024-03, Vol.31 (3), p.e16163-n/a

2024

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Predictive monitoring of temporally-aggregated performance indicators of business processes against low-level streaming events

Information systems (Oxford), 2019-03, Vol.81, p.236-266

2019

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Efficiently interpreting traces of low level events in business process logs

Information systems (Oxford), 2018-03, Vol.73, p.1-24

2018

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Semi-Supervised Discovery of DNN-Based Outcome Predictors from Scarcely-Labeled Process Logs

Business & information systems engineering, 2022-12, Vol.64 (6), p.729-749

2022

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Towards Data- and Compute-Efficient Fake-News Detection: An Approach Combining Active Learning and Pre-Trained Language Models

SN computer science, 2024-06, Vol.5 (5), p.470

2024

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Discovering expressive process models by clustering log traces

IEEE transactions on knowledge and data engineering, 2006-08, Vol.18 (8), p.1010-1027

2006

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IEEE_Xplore

Online and offline classification of traces of event logs on the basis of security risks

Journal of intelligent information systems, 2018-02, Vol.50 (1), p.195-230

2018

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The scent of symbiosis: gut bacteria may affect social interactions in leaf-cutting ants

Animal behaviour, 2019-04, Vol.150, p.239-254

2019

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Mining usage scenarios in business processes: Outlier-aware discovery and run-time prediction

Data & knowledge engineering, 2011-12, Vol.70 (12), p.1005-1029

2011

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Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery

Foundations of Intelligent Systems, p.346-356

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A Cybersecurity Framework for Classifying Non Stationary Data Streams Exploiting Genetic Programming and Ensemble Learning

Numerical Computations: Theory and Algorithms, p.269-277

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Changes in prognosis of the Danish multiple sclerosis population over time

A GP-based ensemble classification framework for time-changing streams of intrusion detection data

AI-Empowered Process Mining for Complex Application Scenarios: Survey and Discussion

Correction to: AI-Empowered Process Mining for Complex Application Scenarios: Survey and Discussion

Socioeconomic status of the elderly MS population compared to the general population: a nationwide Danish matched cross-sectional study

Comparative transcriptomics reveals the conserved building blocks involved in parallel evolution of diverse phenotypic traits in ants

Ant colonies prefer infected over uninfected nest sites

The impact of healthcare systems on the clinical diagnosis and disease-modifying treatment usage in relapse-onset multiple sclerosis: a real-world perspective in five registries across Europe

Proportion and characteristics of secondary progressive multiple sclerosis in five European registries using objective classifiers

An ensemble-based approach to the security-oriented classification of low-level log traces

Process Mining meets argumentation: Explainable interpretations of low-level event logs via abstract argumentation

Pushing More AI Capabilities into Process Mining to Better Deal with Low-Quality Logs

Data- & compute-efficient deviance mining via active learning and fast ensembles

Corrigendum to “Process mining meets argumentation: Explainable interpretations of low-level event logs via abstract argumentation” [Inform. Syst. 107 (2022) 101987]

COVID‐19 vaccination and relapse activity: A nationwide cohort study of patients with multiple sclerosis in Denmark

Predictive monitoring of temporally-aggregated performance indicators of business processes against low-level streaming events

Efficiently interpreting traces of low level events in business process logs

Semi-Supervised Discovery of DNN-Based Outcome Predictors from Scarcely-Labeled Process Logs

Towards Data- and Compute-Efficient Fake-News Detection: An Approach Combining Active Learning and Pre-Trained Language Models

Discovering expressive process models by clustering log traces

Online and offline classification of traces of event logs on the basis of security risks

The scent of symbiosis: gut bacteria may affect social interactions in leaf-cutting ants

Mining usage scenarios in business processes: Outlier-aware discovery and run-time prediction

Combining Active Learning and Fast DNN Ensembles for Process Deviance Discovery

A Cybersecurity Framework for Classifying Non Stationary Data Streams Exploiting Genetic Programming and Ensemble Learning

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