Patrick Zschech
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View article: Inherently Interpretable Machine Learning: A Contrasting Paradigm to Post-hoc Explainable AI
Inherently Interpretable Machine Learning: A Contrasting Paradigm to Post-hoc Explainable AI Open
View article: Decision factors for the selection of AI-based decision support systems—The case of task delegation in prognostics
Decision factors for the selection of AI-based decision support systems—The case of task delegation in prognostics Open
Decision support systems (DSS) integrating artificial intelligence (AI) hold the potential to significantly enhance organizational decision-making performance and speed in areas such as prognostics in machine maintenance. A key issue for o…
View article: Exploring Agentic Artificial Intelligence Systems: Towards a Typological Framework
Exploring Agentic Artificial Intelligence Systems: Towards a Typological Framework Open
Artificial intelligence (AI) systems are evolving beyond passive tools into autonomous agents capable of reasoning, adapting, and acting with minimal human intervention. Despite their growing presence, a structured framework is lacking to …
View article: Designing a Neural Question-Answering System for Times of (Information) Pandemics
Designing a Neural Question-Answering System for Times of (Information) Pandemics Open
Based on Ingwersen’s cognitive model of information retrieval interaction and natural language processing, this article presents (1) design knowledge in the form of requirements, principles, and features, and (2) an artifact to instantiate…
View article: Beware of "Explanations" of AI
Beware of "Explanations" of AI Open
Understanding the decisions made and actions taken by increasingly complex AI system remains a key challenge. This has led to an expanding field of research in explainable artificial intelligence (XAI), highlighting the potential of explan…
View article: CareerBERT: Matching Resumes to ESCO Jobs in a Shared Embedding Space for Generic Job Recommendations
CareerBERT: Matching Resumes to ESCO Jobs in a Shared Embedding Space for Generic Job Recommendations Open
The rapidly evolving labor market, driven by technological advancements and economic shifts, presents significant challenges for traditional job matching and consultation services. In response, we introduce an advanced support tool for car…
View article: CareerBERT: Matching resumes to ESCO jobs in a shared embedding space for generic job recommendations
CareerBERT: Matching resumes to ESCO jobs in a shared embedding space for generic job recommendations Open
View article: Hate Speech and Sentiment of YouTube Video Comments From Public and Private Sources Covering the Israel-Palestine Conflict
Hate Speech and Sentiment of YouTube Video Comments From Public and Private Sources Covering the Israel-Palestine Conflict Open
This study explores the prevalence of hate speech (HS) and sentiment in YouTube video comments concerning the Israel-Palestine conflict by analyzing content from both public and private news sources. The research involved annotating 4983 c…
View article: The Impact of Transparency in AI Systems on Users' Data-Sharing Intentions: A Scenario-Based Experiment
The Impact of Transparency in AI Systems on Users' Data-Sharing Intentions: A Scenario-Based Experiment Open
Artificial Intelligence (AI) systems are frequently employed in online services to provide personalized experiences to users based on large collections of data. However, AI systems can be designed in different ways, with black-box AI syste…
View article: Challenging the Performance-Interpretability Trade-Off: An Evaluation of Interpretable Machine Learning Models
Challenging the Performance-Interpretability Trade-Off: An Evaluation of Interpretable Machine Learning Models Open
Machine learning is permeating every conceivable domain to promote data-driven decision support. The focus is often on advanced black-box models due to their assumed performance advantages, whereas interpretable models are often associated…
View article: Quantifying Visual Properties of GAM Shape Plots: Impact on Perceived Cognitive Load and Interpretability
Quantifying Visual Properties of GAM Shape Plots: Impact on Perceived Cognitive Load and Interpretability Open
Generalized Additive Models (GAMs) offer a balance between performance and interpretability in machine learning. The interpretability aspect of GAMs is expressed through shape plots, representing the model's decision-making process. Howeve…
View article: Challenging the Performance-Interpretability Trade-off: An Evaluation of Interpretable Machine Learning Models
Challenging the Performance-Interpretability Trade-off: An Evaluation of Interpretable Machine Learning Models Open
Machine learning is permeating every conceivable domain to promote data-driven decision support. The focus is often on advanced black-box models due to their assumed performance advantages, whereas interpretable models are often associated…
View article: Leveraging interpretable machine learning in intensive care
Leveraging interpretable machine learning in intensive care Open
View article: Prescriptive analytics systems revised: a systematic literature review from an information systems perspective
Prescriptive analytics systems revised: a systematic literature review from an information systems perspective Open
Prescriptive Analytics Systems (PAS) represent the most mature iteration of business analytics, significantly enhancing organizational decision-making. Recently, research has gained traction, with various technological innovations, includi…
View article: A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis
A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis Open
View article: A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis
A machine learning framework for interpretable predictions in patient pathways: The case of predicting ICU admission for patients with symptoms of sepsis Open
Proactive analysis of patient pathways helps healthcare providers anticipate treatment-related risks, identify outcomes, and allocate resources. Machine learning (ML) can leverage a patient's complete health history to make informed decisi…
View article: IGANN Sparse: Bridging Sparsity and Interpretability with Non-linear Insight
IGANN Sparse: Bridging Sparsity and Interpretability with Non-linear Insight Open
Feature selection is a critical component in predictive analytics that significantly affects the prediction accuracy and interpretability of models. Intrinsic methods for feature selection are built directly into model learning, providing …
View article: Careerbert: Transforming Job Recommendations with Semantic Embeddings
Careerbert: Transforming Job Recommendations with Semantic Embeddings Open
View article: How Risky is my AI System? A Method for Transparent Classification of AI System Descriptions by Regulated AI Risk Categories
How Risky is my AI System? A Method for Transparent Classification of AI System Descriptions by Regulated AI Risk Categories Open
View article: Generative AI
Generative AI Open
View article: Survey and systematization of 3D object detection models and methods
Survey and systematization of 3D object detection models and methods Open
Strong demand for autonomous vehicles and the wide availability of 3D sensors are continuously fueling the proposal of novel methods for 3D object detection. In this paper, we provide a comprehensive survey of recent developments from 2012…
View article: Interpretable generalized additive neural networks
Interpretable generalized additive neural networks Open
View article: Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models
Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models Open
Across many industries, visual quality assurance has transitioned from a manual, labor-intensive, and error-prone task to a fully automated and precise assessment of industrial quality. This transition has been made possible due to advance…
View article: Implementing Digital Responsibility through Information Systems Research: A Delphi Study of Objectives, Activities, and Challenges in IS Research
Implementing Digital Responsibility through Information Systems Research: A Delphi Study of Objectives, Activities, and Challenges in IS Research Open
View article: Artificial Intelligence for Sustainability—A Systematic Review of Information Systems Literature
Artificial Intelligence for Sustainability—A Systematic Review of Information Systems Literature Open
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View article: Generative AI
Generative AI Open
View article: Beyond descriptive taxonomies in data analytics: a systematic evaluation approach for data-driven method pipelines
Beyond descriptive taxonomies in data analytics: a systematic evaluation approach for data-driven method pipelines Open
Taxonomies can serve as a valuable tool to capture dimensions and characteristics of data analytics solutions in a structured manner and thus create transparency about different design options of the technical solution space. However, prev…
View article: GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints
GAM(e) changer or not? An evaluation of interpretable machine learning models based on additive model constraints Open
The number of information systems (IS) studies dealing with explainable artificial intelligence (XAI) is currently exploding as the field demands more transparency about the internal decision logic of machine learning (ML) models. However,…
View article: Where Was COVID-19 First Discovered? Designing a Question-Answering System for Pandemic Situations
Where Was COVID-19 First Discovered? Designing a Question-Answering System for Pandemic Situations Open
The COVID-19 pandemic is accompanied by a massive "infodemic" that makes it hard to identify concise and credible information for COVID-19-related questions, like incubation time, infection rates, or the effectiveness of vaccines. As a nov…
View article: labelCloud: A Lightweight Labeling Tool for Domain-Agnostic 3D Object Detection in Point Clouds
labelCloud: A Lightweight Labeling Tool for Domain-Agnostic 3D Object Detection in Point Clouds Open
Computer-Aided Design and Applications is an international journal on the applications of CAD and CAM. It publishes papers in the general domain of CAD plus in emerging fields like bio-CAD, nano-CAD, soft-CAD, garment-CAD, PLM, PDM, CAD da…