ArticleTranslational oncology2021
Early lung cancer diagnostic biomarker discovery by machine learning methods.
Article in Translational oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 1 of them a synthesis that pooled it.
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Who cites it
78 citing papers in PubMed, 1 synthesis or guideline pooled it, 268 citations in OpenAlex.
- Revolutionizing Lung Cancer Detection: A High-Accuracy Machine Learning Framework for Early Diagnosis.BioMed research international · 2025Pooled it
- Article
- Integration of blood protein-metabolic profiles via machine learning to enable the accurate early detection of non-small cell lung cancer.Respiratory research · 2026Article
- Machine Learning-Driven Metabolomic Biomarker Discovery in Glioblastoma: Advances, Challenges, and Future Directions.International journal of molecular sciences · 2026Review
- The Use of DeepQSAR Models for the Discovery of Peptides With Enhanced Antimicrobial and Antibiofilm Potential.Molecular informatics · 2026Article
- Autophagy-dependent cell death and immune responses induced by heteroleptic copper(II), manganese(II), and silver(I) complexes containing dicarboxylate and 1,10-phenanthroline ligands: novel insights from in vitro and in vivo models.Biometals : an international journal on the role of metal ions in biology, biochemistry, and medicine · 2026Article
- Small data, big challenges: Machine- and deep-learning strategies for data-limited drug discovery.Advanced drug delivery reviews · 2026Review
- Article
- Immunotherapy in Asia: current insights and prospects in Southeast Asia and Malaysia.Frontiers in oncology · 2026Review
- Review: Detection of Cancer Biomarkers from a Clinical Perspective.International journal of molecular sciences · 2025Review
- Multi-omic data integration and exploiting metabolic models using systems biology approach increase precision in subtyping and early diagnosis of cancer.Quantitative biology (Beijing, China) · 2025Article
- Machine learning and WGCNA reveal the PVT1/miR-143-3p/CDK1 ceRNA axis as a key regulator in NSCLC.Biochemistry and biophysics reports · 2025Article
- Cytokine Profiles as Predictive Biomarkers of Disease Severity and Progression in Engineered Stone Silicosis: A Machine Learning Approach.Diagnostics (Basel, Switzerland) · 2025Article
- Machine learning-driven gene expression profiling for lung cancer stage determination.Cancer biomarkers : section A of Disease markers · 2025Article
- Biomarkers for the diagnosis of indeterminate pulmonary nodules: are we there yet?Journal of thoracic disease · 2025Review
- AI-enhanced bioprocess technologies: machine learning implementations from upstream to downstream operations.World journal of microbiology & biotechnology · 2025Review
- Lipids: Driving Forces in the Underlying Biology of Carcinogenesis.ACS pharmacology & translational science · 2025Review
- A Hybrid Sequential Feature Selection Approach for Identifying New Potential mRNA Biomarkers for Usher Syndrome Using Machine Learning.Biomolecules · 2025Article
- Serum taurine affects lung cancer progression by regulating tumor immune escape mediated by the immune microenvironment.Journal of advanced research · 2025Article
- Machine Learning Analysis of the Orbitofrontal Cortex Transcriptome of Human Opioid Users Identifies Shisa7 as a Translational Target Relevant for Heroin Seeking Leveraging a Male Rat Model.Biological psychiatry · 2025Article
18 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
17 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Early diagnosis has been proved to improve survival rate of lung cancer patients. The availability of blood-based screening could increase early lung cancer patient uptake. Our present study attempted to discover Chinese patients' plasma metabolites as diagnostic biomarkers for lung cancer. In this work, we use a pioneering interdisciplinary mechanism, which is firstly applied to lung cancer, to detect early lung cancer diagnostic biomarkers by combining metabolomics and machine learning methods. We collected total 110 lung cancer patients and 43 healthy individuals in our study. Levels of 61 plasma metabolites were from targeted metabolomic study using LC-MS/MS. A specific combination of six metabolic biomarkers note-worthily enabling the discrimination between stage I lung cancer patients and healthy individuals (AUC = 0.989, Sensitivity = 98.1%, Specificity = 100.0%). And the top 5 relative importance metabolic biomarkers developed by FCBF algorithm also could be potential screening biomarkers for early detection of lung cancer. Naïve Bayes is recommended as an exploitable tool for early lung tumor prediction. This research will provide strong support for the feasibility of blood-based screening, and bring a more accurate, quick and integrated application tool for early lung cancer diagnostic. The proposed interdisciplinary method could be adapted to other cancer beyond lung 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 Socratic graph.