Professorship for Information Systems, in particular Data Science
Organisational unit: Professoship
Organisation profile
The Business Informatics working group, in particular Data Science, headed by Prof Dr Burkhardt Funk, is dedicated to the development and application of data-driven methods for decision support in companies and public institutions.
Topics
The research focus lies on the use of data science and machine learning to analyse large amounts of data in order to optimise processes and decisions. A central topic is the development of intelligent systems that support decisions through data-based predictions. Fields of application include healthcare and various operational functions (e.g. marketing, accounting). We have developed approaches for predicting the effectiveness and personalisation of healthcare interventions, methods for extracting knowledge from documents (business documents, scientific papers) and for optimal budget allocation in marketing.
Most downloaded publications
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1
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Development of a Mobile Application for People with Panic Disorder as augmentation for an Internet-based Intervention
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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Online Peer-to-Peer Lending: A Literature Review
Research output: Journal contributions › Scientific review articles › Research
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Towards measuring user engagement in internet interventions for common mental disorders: Workshop on People, Computers, and Psychotherapy
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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A health economic outcome evaluation of an internet-based mobile-supported stress management intervention for employees
Research output: Journal contributions › Journal articles › Research › peer-review
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Effectiveness and Moderators of an Internet-Based Mobile-Supported Stress Management Intervention as a Universal Prevention Approach: Randomized Controlled Trial
Research output: Journal contributions › Journal articles › Research › peer-review
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Predicting Therapy Success and Costs for Personalized Treatment Recommendations Using Baseline Characteristics: Data-Driven Analysis
Research output: Journal contributions › Journal articles › Research › peer-review
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Developing a Process for the Analysis of User Journeys and the Prediction of Dropout in Digital Health Interventions: Machine Learning Approach
Research output: Journal contributions › Conference article in journal › Research › peer-review
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Einsatz von Workflow-Managementsystemen in der Hochschulverwaltung
Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research
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9
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Personalization strategies in digital mental health interventions: a systematic review and conceptual framework for depressive symptoms
Research output: Journal contributions › Scientific review articles › Research
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Evaluating a hybrid web-based training program for panic disorder and agoraphobia: Randomized controlled trial
Research output: Journal contributions › Journal articles › Research › peer-review
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11
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Economic Evaluation of an Internet-Based Stress Management Intervention Alongside a Randomized Controlled Trial
Research output: Journal contributions › Journal articles › Research › peer-review
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12
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Entwicklung einer Fallstudie für die Lehre im IT-gestützten Personalmanagement
Research output: Contributions to collected editions/works › Contributions to collected editions/anthologies › Research
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13
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Datenschutzbedenken in Sozialen Netzen -: ein Strukturgleichungsmodell
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review
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14
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Quality and Adoption of COVID-19 Tracing Apps and Recommendations for Development: Systematic Interdisciplinary Review of European Apps
Research output: Journal contributions › Scientific review articles › Research
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15
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A systematic literature review of machine learning canvases
Research output: Contributions to collected editions/works › Article in conference proceedings › Research › peer-review