Mass spectrometry imaging: a review of emerging advancements and future insights
Mass spectrometry imaging (MSI) is a powerful tool that enables untargeted investigations
into the spatial distribution of molecular species in a variety of samples. It has the capability …
into the spatial distribution of molecular species in a variety of samples. It has the capability …
Unsupervised machine learning for exploratory data analysis in imaging mass spectrometry
N Verbeeck, RM Caprioli… - Mass spectrometry …, 2020 - Wiley Online Library
Imaging mass spectrometry (IMS) is a rapidly advancing molecular imaging modality that
can map the spatial distribution of molecules with high chemical specificity. IMS does not …
can map the spatial distribution of molecules with high chemical specificity. IMS does not …
Peak learning of mass spectrometry imaging data using artificial neural networks
WM Abdelmoula, BGC Lopez, EC Randall… - Nature …, 2021 - nature.com
Mass spectrometry imaging (MSI) is an emerging technology that holds potential for
improving, biomarker discovery, metabolomics research, pharmaceutical applications and …
improving, biomarker discovery, metabolomics research, pharmaceutical applications and …
Deep learning for tumor classification in imaging mass spectrometry
J Behrmann, C Etmann, T Boskamp… - …, 2018 - academic.oup.com
Motivation Tumor classification using imaging mass spectrometry (IMS) data has a high
potential for future applications in pathology. Due to the complexity and size of the data …
potential for future applications in pathology. Due to the complexity and size of the data …
Evaluation of distance metrics and spatial autocorrelation in uniform manifold approximation and projection applied to mass spectrometry imaging data
In this work, uniform manifold approximation and projection (UMAP) is applied for nonlinear
dimensionality reduction and visualization of mass spectrometry imaging (MSI) data. We …
dimensionality reduction and visualization of mass spectrometry imaging (MSI) data. We …
Impact of autoencoder based compact representation on emotion detection from audio
Emotion recognition from speech has its fair share of applications and consequently
extensive research has been done over the past few years in this interesting field. However …
extensive research has been done over the past few years in this interesting field. However …
Deep learning for mining protein data
The recent emergence of deep learning to characterize complex patterns of protein big data
reveals its potential to address the classic challenges in the field of protein data mining …
reveals its potential to address the classic challenges in the field of protein data mining …
MAIA—A machine learning assisted image annotation method for environmental monitoring and exploration
Digital imaging has become one of the most important techniques in environmental
monitoring and exploration. In the case of the marine environment, mobile platforms such as …
monitoring and exploration. In the case of the marine environment, mobile platforms such as …
Spatially aware clustering of ion images in mass spectrometry imaging data using deep learning
Computational analysis is crucial to capitalize on the wealth of spatio-molecular information
generated by mass spectrometry imaging (MSI) experiments. Currently, the spatial …
generated by mass spectrometry imaging (MSI) experiments. Currently, the spatial …
Toward enhanced prediction of high‐impact solar energetic particle events using multimodal time series data fusion models
P Hosseinzadeh, S Filali Boubrahimi… - Space Weather, 2024 - Wiley Online Library
Solar energetic particle (SEP) events, originating from solar flares and Coronal Mass
Ejections, present significant hazards to space exploration and technology on Earth …
Ejections, present significant hazards to space exploration and technology on Earth …