mlsanityData to 7 Oct 2026

Identification of Prognostic Biomarkers for Stage III Non-Small Cell Lung Carcinoma in Female Nonsmokers Using Machine Learning

arXiv 2408.16068 ↗First posted 28 Aug 2024q-bio.GN cs.AI stat.MLcited by 17

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Abstract (arXiv)

Lung cancer remains a leading cause of cancer-related deaths globally, with non-small cell lung cancer (NSCLC) being the most common subtype. This study aimed to identify key biomarkers associated with stage III NSCLC in non-smoking females using gene expression profiling from the GDS3837 dataset. Utilizing XGBoost, a machine learning algorithm, the analysis achieved a strong predictive performance with an AUC score of 0.835. The top biomarkers identified - CCAAT enhancer binding protein alpha (C/EBP-alpha), lactate dehydrogenase A4 (LDHA), UNC-45 myosin chaperone B (UNC-45B), checkpoint kinase 1 (CHK1), and hypoxia-inducible factor 1 subunit alpha (HIF-1-alpha) - have been validated in the literature as being significantly linked to lung cancer. These findings highlight the potential of these biomarkers for early diagnosis and personalized therapy, emphasizing the value of integrating machine learning with molecular profiling in cancer research.

Key facts. Cited by 17 papers in the map (data through 7 Oct 2026). Builds on 13 of its 30 references that are in the map. First posted on arXiv 28 Aug 2024.

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13 of 30 references.

References · 13

  1. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,120
  2. 2023VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understandingcited by 62
  3. 2021Pareto Self-Supervised Training for Few-Shot Learningcited by 52
  4. 2024Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitatecited by 46
  5. 2023MmAP : Multi-modal Alignment Prompt for Cross-domain Multi-task Learningcited by 41
  6. 2019The FacT: Taming Latent Factor Models for Explainability with Factorization Treescited by 27
  7. 2023LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inferencecited by 26
  8. 2024Harnessing XGBoost for Robust Biomarker Selection of Obsessive-Compulsive Disorder (OCD) from Adolescent Brain Cognitive Development (ABCD) datacited by 26
  9. 2023MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Trainingcited by 25
  10. 2024CU-Net: a U-Net architecture for efficient brain-tumor segmentation on BraTS 2019 datasetcited by 24
  11. 2024Application of Multimodal Fusion Deep Learning Model in Disease Recognitioncited by 12
  12. 2024Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENNcited by 10
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  1. 2024Advanced Payment Security System:XGBoost, LightGBM and SMOTE Integratedcited by 8

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