ReviewFrontiers in artificial intelligence2021
Applications of Topological Data Analysis in Oncology.
Review in Frontiers in artificial intelligence, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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.
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Who cites it
19 citing papers in PubMed.
- Topology-Aware Deep Learning on Higher-Order Structures for Drug Response Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Slide-free FIBI histology for improved quantitative vascular network analysis in breast cancer: Integrating vessel geometry and topology metrics.Journal of pathology informatics · 2026Article
- Topological feature-driven TabPFN model for prediction of enlarged hemorrhage and edema after tumor resection in meningiomas.Frontiers in medicine · 2026Article
- Cancer and Aging Biomarkers: Classification, Early Detection Technologies and Emerging Research Trends.Biosensors · 2025Review
- Unraveling the Invisible: Topological Data Analysis as the New Frontier in Radiology's Diagnostic Arsenal.Tomography (Ann Arbor, Mich.) · 2025Article
- Topological data analysis in single cell biology.Frontiers in immunology · 2025Review
- Topological data analysis captures horizontal gene transfer in antimicrobial resistance gene families among clinically relevant bacteria.Frontiers in microbiology · 2025Article
- TopoLoop: A new tool for chromatin loop detection in live cells via single-particle tracking.The Journal of chemical physics · 2024Article
- Article
- Dissecting glial scar formation by spatial point pattern and topological data analysis.Scientific reports · 2024Article
- Advancing Precision Medicine: Algebraic Topology and Differential Geometry in Radiology and Computational Pathology.Laboratory investigation; a journal of technical methods and pathology · 2024Review
- The shape of cancer relapse: Topological data analysis predicts recurrence in paediatric acute lymphoblastic leukaemia.PLoS computational biology · 2023Article
- Spatiochemical Characterization of the Pancreas Using Mass Spectrometry Imaging and Topological Data Analysis.Analytical chemistry · 2023Article
- Supervised topological data analysis for MALDI mass spectrometry imaging applications.BMC bioinformatics · 2023Article
- Effect of prior treatments on post-CDK 4/6 inhibitor survival in hormone receptor-positive breast cancer.Breast cancer research and treatment · 2023Article
- Multiscale topology characterizes dynamic tumor vascular networks.Science advances · 2022Article
- Topological data analysis in biomedicine: A review.Journal of biomedical informatics · 2022Review
- Time-to-Event Machine Learning Model Incorporating MRI-Derived Intratumoral Heterogeneity Score for Predicting Invasive Breast Cancer Recurrence: A Dual-Center Study.Technology in cancer research & treatmentArticle
- Decoding Intratumoral Heterogeneity in Breast Cancer: The Evolution From Radiomics to Topological Quantification for Predicting Lymphovascular Invasion.Cancer control : journal of the Moffitt Cancer CenterReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The emergence of the information age in the last few decades brought with it an explosion of biomedical data. But with great power comes great responsibility: there is now a pressing need for new data analysis algorithms to be developed to make sense of the data and transform this information into knowledge which can be directly translated into the clinic. Topological data analysis (TDA) provides a promising path forward: using tools from the mathematical field of algebraic topology, TDA provides a framework to extract insights into the often high-dimensional, incomplete, and noisy nature of biomedical data. Nowhere is this more evident than in the field of oncology, where patient-specific data is routinely presented to clinicians in a variety of forms, from imaging to single cell genomic sequencing. In this review, we focus on applications involving persistent homology, one of the main tools of TDA. We describe some recent successes of TDA in oncology, specifically in predicting treatment responses and prognosis, tumor segmentation and computer-aided diagnosis, disease classification, and cellular architecture determination. We also provide suggestions on avenues for future research including utilizing TDA to analyze cancer time-series data such as gene expression changes during pathogenesis, investigation of the relation between angiogenic vessel structure and treatment efficacy from imaging data, and experimental confirmation that geometric and topological connectivity implies functional connectivity in the context of cancer.
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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.