Marc Claesen
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View article: Multi-omics integration and batch correction using a modality-agnostic deep learning framework
Multi-omics integration and batch correction using a modality-agnostic deep learning framework Open
State-of-the-art biotechnologies allow the detection of different molecular species on the same biological sample, generating complex highly-dimensional multi-modal datasets. Gaining a holistic understanding of biological phenomena, such a…
View article: Spatial Transcriptomics of Schizophrenia Insular Cortex Reveals Blood-Brain Barrier Hyperglycolysis and Increased Parenchymal Mitochondrial Respiration
Spatial Transcriptomics of Schizophrenia Insular Cortex Reveals Blood-Brain Barrier Hyperglycolysis and Increased Parenchymal Mitochondrial Respiration Open
Introduction The blood-brain barrier (BBB) acts as the metabolic and immunological gatekeeper of the brain. Since alterations in neurometabolism and neuroimmunity are found in schizophrenia-spectrum disorders (SSD) which are hypothesised t…
View article: 213 Concordance assessment study of Xenium and Visium spatial transcriptomics assays using multiple carcinoma samples
213 Concordance assessment study of Xenium and Visium spatial transcriptomics assays using multiple carcinoma samples Open
View article: 91 Using spatial multi-omics to investigate the contribution of tumor microenvironment to minimal residual disease and intrinsic chemoresistance of high-grade serous ovarian cancer
91 Using spatial multi-omics to investigate the contribution of tumor microenvironment to minimal residual disease and intrinsic chemoresistance of high-grade serous ovarian cancer Open
View article: 182 Xenium in situ analysis and reproducibility study of multiple carcinomas for clinical studies
182 Xenium in situ analysis and reproducibility study of multiple carcinomas for clinical studies Open
View article: 832 Reproducibility and quality assessment study of xenium and visium spatial transcriptomics assays from multiple carcinoma samples via an end-to-end spatial multi-omics platform weave
832 Reproducibility and quality assessment study of xenium and visium spatial transcriptomics assays from multiple carcinoma samples via an end-to-end spatial multi-omics platform weave Open
View article: Multimodal MALDI imaging mass spectrometry for improved diagnosis of melanoma
Multimodal MALDI imaging mass spectrometry for improved diagnosis of melanoma Open
Imaging mass spectrometry (IMS) provides promising avenues to augment histopathological investigation with rich spatio-molecular information. We have previously developed a classification model to differentiate melanoma from nevi lesions b…
View article: Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture
Toward Omics-Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue Using a Multiclass Internal Standard Mixture Open
Mass spectrometry imaging (MSI) has accelerated our understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focused on a sin…
View article: Integration of Multiple Spatial Omics Modalities Reveals Unique Insights into Molecular Heterogeneity of Prostate Cancer
Integration of Multiple Spatial Omics Modalities Reveals Unique Insights into Molecular Heterogeneity of Prostate Cancer Open
Recent advances in spatial omics methods are revolutionising biomedical research by enabling detailed molecular analyses of cells and their interactions in their native state. As most technologies capture only a specific type of molecules,…
View article: Omics Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue using a Multi-Class Internal Standard Mixture
Omics Scale Quantitative Mass Spectrometry Imaging of Lipids in Brain Tissue using a Multi-Class Internal Standard Mixture Open
Mass spectrometry imaging (MSI) has accelerated the understanding of lipid metabolism and spatial distribution in tissues and cells. However, few MSI studies have approached lipid imaging quantitatively and those that have focus on a singl…
View article: Multimodal MALDI imaging mass spectrometry for improved diagnosis of melanoma
Multimodal MALDI imaging mass spectrometry for improved diagnosis of melanoma Open
Imaging mass spectrometry (IMS) provides promising avenues to augment histopathological investigation with rich spatio-molecular information. We have previously developed a classification model to differentiate melanoma from nevi lesions b…
View article: Diagnosis of melanoma by imaging mass spectrometry: Development and validation of a melanoma prediction model
Diagnosis of melanoma by imaging mass spectrometry: Development and validation of a melanoma prediction model Open
Background The definitive diagnosis of melanocytic neoplasia using solely histopathologic evaluation can be challenging. Novel techniques that objectively confirm diagnoses are needed. This study details the development and validation of a…
View article: Spatially aware clustering of ion images in mass spectrometry imaging data using deep learning
Spatially aware clustering of ion images in mass spectrometry imaging data using deep learning Open
Computational analysis is crucial to capitalize on the wealth of spatio-molecular information generated by mass spectrometry imaging (MSI) experiments. Currently, the spatial information available in MSI data is often under-utilized, due t…
View article: Spatially-Aware Clustering of Ion Images in Mass Spectrometry Imaging Data Using Deep Learning
Spatially-Aware Clustering of Ion Images in Mass Spectrometry Imaging Data Using Deep Learning Open
Computational analysis is crucial to capitalize on the wealth of spatio-molecular information generated by mass spectrometry imaging (MSI) experiments. Currently, the spatial information available in MSI data is often under-utilized, due t…
View article: Evaluation of Distance Metrics and Spatial Autocorrelation in Uniform Manifold Approximation and Projection Applied to Mass Spectrometry Imaging Data
Evaluation of Distance Metrics and Spatial Autocorrelation in Uniform Manifold Approximation and Projection Applied to Mass Spectrometry Imaging Data Open
In this work, uniform manifold approximation and projection (UMAP) is applied for nonlinear dimensionality reduction and visualization of mass spectrometry imaging (MSI) data. We evaluate the performance of the UMAP algorithm on MSI data s…
View article: A FULLY AUTOMATED PIPELINE FOR CLASSIFICATION TASKS WITH AN APPLICATION TO REMOTE SENSING
A FULLY AUTOMATED PIPELINE FOR CLASSIFICATION TASKS WITH AN APPLICATION TO REMOTE SENSING Open
Nowadays deep learning has been intensively in spotlight owing to its great victories at major competitions, which undeservedly pushed ‘shallow’ machine learning methods, relatively naive/handy algorithms commonly used by industrial engine…
View article: Mortality in Individuals Treated With Glucose-Lowering Agents: A Large, Controlled Cohort Study
Mortality in Individuals Treated With Glucose-Lowering Agents: A Large, Controlled Cohort Study Open
Differences exist in 5-year survival of patients on GLA, at least partly driven by the risk profile of the individuals themselves. Metformin use was associated with lowest 5-year mortality risk and statins dramatically lowered 5-year morta…
View article: Building Classifiers to Predict the Start of Glucose-Lowering Pharmacotherapy Using Belgian Health Expenditure Data
Building Classifiers to Predict the Start of Glucose-Lowering Pharmacotherapy Using Belgian Health Expenditure Data Open
Early diagnosis is important for type 2 diabetes (T2D) to improve patient prognosis, prevent complications and reduce long-term treatment costs. We present a novel risk profiling approach based exclusively on health expenditure data that i…
View article: Building Classifiers to Predict the Start of Glucose-Lowering\n Pharmacotherapy Using Belgian Health Expenditure Data
Building Classifiers to Predict the Start of Glucose-Lowering\n Pharmacotherapy Using Belgian Health Expenditure Data Open
Early diagnosis is important for type 2 diabetes (T2D) to improve patient\nprognosis, prevent complications and reduce long-term treatment costs. We\npresent a novel risk profiling approach based exclusively on health expenditure\ndata tha…
View article: Assessing binary classifiers using only positive and unlabeled data
Assessing binary classifiers using only positive and unlabeled data Open
Assessing the performance of a learned model is a crucial part of machine learning. However, in some domains only positive and unlabeled examples are available, which prohibits the use of most standard evaluation metrics. We propose an app…
View article: A robust ensemble approach to learn from positive and unlabeled data using SVM base models
A robust ensemble approach to learn from positive and unlabeled data using SVM base models Open
View article: Hyperparameter Search in Machine Learning
Hyperparameter Search in Machine Learning Open
We introduce the hyperparameter search problem in the field of machine learning and discuss its main challenges from an optimization perspective. Machine learning methods attempt to build models that capture some element of interest based …