ArticleCancers2021
Cancer Tissue Classification Using Supervised Machine Learning Applied to MALDI Mass Spectrometry Imaging.
Article in Cancers, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 30 citations in OpenAlex.
- Portable Multispectral Optoelectronic System for Thyroid Cancer Detection.Sensors (Basel, Switzerland) · 2026Article
- Review
- Interpreting MALDI imaging data for rare types of ampullary cancer using machine learning.NPJ systems biology and applications · 2026Article
- Intraoperative Mass Spectrometry in Oncology: Technologies, Clinical Applications, and Challenges.Molecules (Basel, Switzerland) · 2026Review
- Research Progress on the Application of Mass Spectrometry Imaging Technology in Cerebral Disease.Life (Basel, Switzerland) · 2026Review
- Article
- Mass Spectrometry Imaging for Spatial Ingredient Classification in Plant-Based Food.Journal of the American Society for Mass Spectrometry · 2025Article
- Spatially resolved metabolomics: From metabolite mapping to function visualising.Clinical and translational medicine · 2024Review
- An Update on the Use of Artificial Intelligence in Digital Pathology for Oral Epithelial Dysplasia Research.Head and neck pathology · 2024Review
- Classification of Pancreatic Ductal Adenocarcinoma Using MALDI Mass Spectrometry Imaging Combined with Neural Networks.Cancers · 2023Article
- Mass spectrometry imaging in gynecological cancers: the best is yet to come.Cancer cell international · 2022Review
- Review
- Boron Delivery to Brain Cells via Cerebrospinal Fluid (CSF) Circulation in BNCT of Brain-Tumor-Model Rats-Ex Vivo Imaging of BPA Using MALDI Mass Spectrometry Imaging.Life (Basel, Switzerland) · 2022Article
- Deep Learning on Histopathological Images for Colorectal Cancer Diagnosis: A Systematic Review.Diagnostics (Basel, Switzerland) · 2022Review
- Applications of spatially resolved omics in the field of endocrine tumors.Frontiers in endocrinology · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 5 institutions in 3 countries.
Funding
Abstract
Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) can determine the spatial distribution of analytes such as protein distributions in a tissue section according to their mass-to-charge ratio. Here, we explored the clinical potential of machine learning (ML) applied to MALDI MSI data for cancer diagnostic classification using tissue microarrays (TMAs) on 302 colorectal (CRC) and 257 endometrial cancer (EC)) patients. ML based on deep neural networks discriminated colorectal tumour from normal tissue with an overall accuracy of 98% in balanced cross-validation (98.2% sensitivity and 98.6% specificity). Moreover, our machine learning approach predicted the presence of lymph node metastasis (LNM) for primary tumours of EC with an accuracy of 80% (90% sensitivity and 69% specificity). Our results demonstrate the capability of MALDI MSI for complementing classic histopathological examination for cancer diagnostic applications.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.