Mathias Kraus
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View article: Listening to Hypoglycemia: Voice as a Biomarker for Detection of a Medical Emergency Using Machine Learning
Listening to Hypoglycemia: Voice as a Biomarker for Detection of a Medical Emergency Using Machine Learning Open
OBJECTIVE Hypoglycemia is a hazardous diabetes-related emergency. We aimed to develop a machine learning (ML) approach for noninvasive hypoglycemia detection using voice data. RESEARCH DESIGN AND METHODS We collected voice data (540 record…
View article: Navigating the Rashomon Effect: How Personalization Can Help Adjust Interpretable Machine Learning Models to Individual Users
Navigating the Rashomon Effect: How Personalization Can Help Adjust Interpretable Machine Learning Models to Individual Users Open
The Rashomon effect describes the observation that in machine learning (ML) multiple models often achieve similar predictive performance while explaining the underlying relationships in different ways. This observation holds even for intri…
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: 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: Benchmarking Cluster-Then-Predict Models to Challenge Prevailing Global Machine Learning Models
Benchmarking Cluster-Then-Predict Models to Challenge Prevailing Global Machine Learning Models Open
In predictive analytics domains, such as healthcare, marketing and finance, data exhibits inherent segmentation, like patient, customer and market segments. Powerful global models, like XGBoost or Catboost, offer high predictive qualities,…
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
In healthcare, especially within intensive care units (ICU), informed decision-making by medical professionals is crucial due to the complexity of medical data. Healthcare analytics seeks to support these decisions by generating accurate p…
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: How cheap talk in climate disclosures relates to climate initiatives, corporate emissions, and reputation risk
How cheap talk in climate disclosures relates to climate initiatives, corporate emissions, and reputation risk Open
Navigating the complex landscape of corporate climate disclosures and their real impacts is crucial for managing climate-related financial risks. However, current disclosures oftentimes suffer from imprecision, inaccuracy, and greenwashing…
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: Multimodal In-Vehicle Hypoglycemia Warning for Drivers With Type 1 Diabetes: Design and Evaluation in Simulated and Real-World Driving
Multimodal In-Vehicle Hypoglycemia Warning for Drivers With Type 1 Diabetes: Design and Evaluation in Simulated and Real-World Driving Open
Background Hypoglycemia threatens cognitive function and driving safety. Previous research investigated in-vehicle voice assistants as hypoglycemia warnings. However, they could startle drivers. To address this, we combine voice warnings w…
View article: Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering
Towards Faithful and Robust LLM Specialists for Evidence-Based Question-Answering Open
Advances towards more faithful and traceable answers of Large Language Models (LLMs) are crucial for various research and practical endeavors. One avenue in reaching this goal is basing the answers on reliable sources. However, this Eviden…
View article: A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions
A Globally Convergent Algorithm for Neural Network Parameter Optimization Based on Difference-of-Convex Functions Open
We propose an algorithm for optimizing the parameters of single hidden layer neural networks. Specifically, we derive a blockwise difference-of-convex (DC) functions representation of the objective function. Based on the latter, we propose…
View article: Bridging the gap in ESG measurement: Using NLP to quantify environmental, social, and governance communication
Bridging the gap in ESG measurement: Using NLP to quantify environmental, social, and governance communication Open
Environmental, social, and governance (ESG) criteria take a central role in fostering sustainable development in economies. This paper introduces a class of novel Natural Language Processing (NLP) models to assess corporate disclosures in …