Markus Reischl
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View article: Rapid deep-learning-based optical measurement of printed linear structures
Rapid deep-learning-based optical measurement of printed linear structures Open
Conventional optical measurement techniques are beneficial in automated manufacturing processes due to their fast and non-intrusive operation. However, they require sophisticated and expensive equipment as well as increased personnel quali…
View article: Rapid deep-learning-based optical measurement of printed linear structures
Rapid deep-learning-based optical measurement of printed linear structures Open
Conventional optical measurement techniques are beneficial in automated manufacturing processes due to their fast and non-intrusive operation. However, they require sophisticated and expensive equipment as well as increased personnel quali…
View article: ML-Driven Contamination Classification for XPS Analysis of PLA Surfaces
ML-Driven Contamination Classification for XPS Analysis of PLA Surfaces Open
As materials such as Poly-Lactic Acid (PLA) have become a significant part of medical production and research, it is important that the resulting products adhere to strict regulations concerning contaminations. A wide variety of methods ar…
View article: Bayesian Optimization Driven Cancer Drug Dose-Response Curve Discovery
Bayesian Optimization Driven Cancer Drug Dose-Response Curve Discovery Open
Screening of cancer drugs in personalized medicine and cancer treatment research is expensive. Large libraries of compounds must be evaluated, and multiple doses for each compound need to be tested to assess their viability. We introduce a…
View article: Automatic Labeling of Multi-Modal Sensor Training Data for Hand Gesture Analysis
Automatic Labeling of Multi-Modal Sensor Training Data for Hand Gesture Analysis Open
Hand gesture recognition is an important task in human-machine interaction, enabling intuitive and accessible control methods across various applications, including assistive technologies, virtual reality or sign language translation. The …
View article: Large Means Left: Political Bias in Large Language Models Increases with Their Number of Parameters
Large Means Left: Political Bias in Large Language Models Increases with Their Number of Parameters Open
With the increasing prevalence of artificial intelligence, careful evaluation of inherent biases needs to be conducted to form the basis for alleviating the effects these predispositions can have on users. Large language models (LLMs) are …
View article: Assessing political bias in large language models
Assessing political bias in large language models Open
Evaluating bias in Large Language Models (LLMs) has become a pivotal issue in current Artificial Intelligence (AI) research due to their significant impact on societal dynamics. Recognizing political bias in LLMs is particularly important …
View article: ASAP: Automated Style-Aware Similarity Measurement for Selection of Annotated Pre-Training Datasets in 2D Biomedical Imaging
ASAP: Automated Style-Aware Similarity Measurement for Selection of Annotated Pre-Training Datasets in 2D Biomedical Imaging Open
Medical imaging scenarios are characterized by varying image modalities, several organs/cell shapes, and little annotated data because of the expertise required for labeling. The successful use of state-of-the-art deep-learning approaches …
View article: ML-Based XPS Quantification Supported by Synthetic Dataset Generation
ML-Based XPS Quantification Supported by Synthetic Dataset Generation Open
With growing interest in laboratory automation and high-throughput systems, the amount of generated experimental data is rapidly increasing while analysis methods still require many manual work hours from experts. This is prevalent in X-ra…
View article: Using Large Language Models for Extracting Structured Information From Scientific Texts
Using Large Language Models for Extracting Structured Information From Scientific Texts Open
Extracting structured information from scientific works is challenging as sought parameters or properties are often scattered across lengthy texts. We introduce a novel iterative approach using Large Language Models (LLMs) to automate this…
View article: Quantitative Convolutional Neural Network Based Multi-Phase XRD Pattern Analysis
Quantitative Convolutional Neural Network Based Multi-Phase XRD Pattern Analysis Open
X-ray diffraction (XRD) is commonly used to analyze phase compositions of crystalline samples. Medical applications include the analysis of biotechnological materials and gall- and kidney stones, where composition can inform pathology asse…
View article: Highly Parallel and High‐Throughput Nanoliter‐Scale Liquid, Cell, and Spheroid Manipulation on Droplet Microarray
Highly Parallel and High‐Throughput Nanoliter‐Scale Liquid, Cell, and Spheroid Manipulation on Droplet Microarray Open
The droplet microarray (DMA) platform is a powerful tool for high‐throughput biological and chemical applications, enabling miniaturization and parallelization of experimental processes. Capable of holding hundreds of nanoliter droplets, i…
View article: OS04.7.A PRESERVATION OF FERTILITY AND FAMILY PLANNING IN PATIENTS WITH LOW-GRADE GLIOMA
OS04.7.A PRESERVATION OF FERTILITY AND FAMILY PLANNING IN PATIENTS WITH LOW-GRADE GLIOMA Open
BACKGROUND Patients suffering from a Low-grade glioma (LGG) will require adjuvant treatment at some stage of their course of disease which is a mayor impact for fertility and family planning. Given the predominantly young age of patients a…
View article: Adaptable Accelerometer Signal Processing Pipelines for Smartphone based Evenness Estimation
Adaptable Accelerometer Signal Processing Pipelines for Smartphone based Evenness Estimation Open
Evenness is an essential indicator of road quality. Accelerometer sensors in smartphones offer an accessible and cost-efficient solution for monitoring road evenness. However, the accelerometer signal from smartphones is influenced by vari…
View article: From in vitro to in silico: a pipeline for generating virtual tissue simulations from real image data
From in vitro to in silico: a pipeline for generating virtual tissue simulations from real image data Open
3D cell culture models replicate tissue complexity and aim to study cellular interactions and responses in a more physiologically relevant environment compared to traditional 2D cultures. However, the spherical structure of these models ma…
View article: Improving 3D deep learning segmentation with biophysically motivated cell synthesis
Improving 3D deep learning segmentation with biophysically motivated cell synthesis Open
Biomedical research increasingly relies on 3D cell culture models and AI-based analysis can potentially facilitate a detailed and accurate feature extraction on a single-cell level. However, this requires for a precise segmentation of 3D c…
View article: A multiparametric analysis including single-cell and subcellular feature assessment reveals differential behavior of spheroid cultures on distinct ultra-low attachment plate types
A multiparametric analysis including single-cell and subcellular feature assessment reveals differential behavior of spheroid cultures on distinct ultra-low attachment plate types Open
Spheroids have become principal three-dimensional models to study cancer, developmental processes, and drug efficacy. Single-cell analysis techniques have emerged as ideal tools to gauge the complexity of cellular responses in these models…
View article: Using the High-Entropy Approach to Obtain Multimetal Oxide Nanozymes: Library Synthesis, <i>In Silico</i> Structure–Activity, and Immunoassay Performance
Using the High-Entropy Approach to Obtain Multimetal Oxide Nanozymes: Library Synthesis, <i>In Silico</i> Structure–Activity, and Immunoassay Performance Open
High-entropy nanomaterials exhibit exceptional mechanical, physical, and chemical properties, finding applications in many industries. Peroxidases are metalloenzymes that accelerate the decomposition of hydrogen peroxide. This study uses t…
View article: Uncertainty-aware particle segmentation for electron microscopy at varied length scales
Uncertainty-aware particle segmentation for electron microscopy at varied length scales Open
Electron microscopy is indispensable for examining the morphology and composition of solid materials at the sub-micron scale. To study the powder samples that are widely used in materials development, scanning electron microscopes (SEMs) a…
View article: Image-based recognition of parasitoid wasps using advanced neural networks
Image-based recognition of parasitoid wasps using advanced neural networks Open
Hymenoptera has some of the highest diversity and number of individuals among insects. Many of these species potentially play key roles as food sources, pest controllers and pollinators. However, little is known about the diversity and bio…
View article: Assessing Political Bias in Large Language Models
Assessing Political Bias in Large Language Models Open
The assessment of bias within Large Language Models (LLMs) has emerged as a critical concern in the contemporary discourse surrounding Artificial Intelligence (AI) in the context of their potential impact on societal dynamics. Recognizing …
View article: A Multiparametric Analysis Reveals Differential Behavior of Spheroid Cultures on Distinct Ultra-Low Attachment Plates Types
A Multiparametric Analysis Reveals Differential Behavior of Spheroid Cultures on Distinct Ultra-Low Attachment Plates Types Open
Spheroids have become principal three-dimensional biological models to study cancer, developmental processes, and drug efficacy. For spheroid generation, ultra-low attachment plates are noteworthy due to their simplicity, compatibility wit…
View article: A review of adaptable conventional image processing pipelines and deep learning on limited datasets
A review of adaptable conventional image processing pipelines and deep learning on limited datasets Open
The objective of this paper is to study the impact of limited datasets on deep learning techniques and conventional methods in semantic image segmentation and to conduct a comparative analysis in order to determine the optimal scenario for…
View article: Surface-Patterned DNA Origami Rulers Reveal Nanoscale Distance Dependency of the Epidermal Growth Factor Receptor Activation
Surface-Patterned DNA Origami Rulers Reveal Nanoscale Distance Dependency of the Epidermal Growth Factor Receptor Activation Open
The nanoscale arrangement of ligands can have a major effect on the activation of membrane receptor proteins and thus cellular communication mechanisms. Here we report on the technological development and use of tailored DNA origami-based …
View article: Accelerating Materials Discovery: Automated Identification of Prospects from X‐Ray Diffraction Data in Fast Screening Experiments
Accelerating Materials Discovery: Automated Identification of Prospects from X‐Ray Diffraction Data in Fast Screening Experiments Open
New materials are frequently synthesized and optimized with the explicit intention to improve their properties to meet the ever‐increasing societal requirements for high‐performance and energy‐efficient electronics, new battery concepts, b…