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

arXiv: https://arxiv.org/abs/2408.16068 · HTML: https://mlsanity.com/paper/2408.16068/

## Key facts

- Cited by 17 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 30 references that are in the map.
- First posted on arXiv 28 Aug 2024.

## Builds on (most cited first, 13 of 13)

- [XGBoost: A Scalable Tree Boosting System](https://mlsanity.com/paper/1603.02754/) (2016)
- [VMT-Adapter: Parameter-Efficient Transfer Learning for Multi-Task Dense Scene Understanding](https://mlsanity.com/paper/2312.08733/) (2023)
- [Pareto Self-Supervised Training for Few-Shot Learning](https://mlsanity.com/paper/2104.07841/) (2021)
- [Learning from Teaching Regularization: Generalizable Correlations Should be Easy to Imitate](https://mlsanity.com/paper/2402.02769/) (2024)
- [MmAP : Multi-modal Alignment Prompt for Cross-domain Multi-task Learning](https://mlsanity.com/paper/2312.08636/) (2023)
- [The FacT: Taming Latent Factor Models for Explainability with Factorization Trees](https://mlsanity.com/paper/1906.02037/) (2019)
- [LinGCN: Structural Linearized Graph Convolutional Network for Homomorphically Encrypted Inference](https://mlsanity.com/paper/2309.14331/) (2023)
- [Harnessing XGBoost for Robust Biomarker Selection of Obsessive-Compulsive Disorder (OCD) from Adolescent Brain Cognitive Development (ABCD) data](https://mlsanity.com/paper/2407.00028/) (2024)
- [MaxK-GNN: Extremely Fast GPU Kernel Design for Accelerating Graph Neural Networks Training](https://mlsanity.com/paper/2312.08656/) (2023)
- [CU-Net: a U-Net architecture for efficient brain-tumor segmentation on BraTS 2019 dataset](https://mlsanity.com/paper/2406.13113/) (2024)
- [Application of Multimodal Fusion Deep Learning Model in Disease Recognition](https://mlsanity.com/paper/2406.18546/) (2024)
- [Advanced User Credit Risk Prediction Model using LightGBM, XGBoost and Tabnet with SMOTEENN](https://mlsanity.com/paper/2408.03497/) (2024)
- [Advanced Payment Security System:XGBoost, LightGBM and SMOTE Integrated](https://mlsanity.com/paper/2406.04658/) (2024)

## Built on by (most cited first, 17 of 17)

- [Mitigating the Risk of Health Inequity Exacerbated by Large Language Models](https://mlsanity.com/paper/2410.05180/) (2024)
- [Harnessing LLMs for API Interactions: A Framework for Classification and Synthetic Data Generation](https://mlsanity.com/paper/2409.11703/) (2024)
- [Deep Reinforcement Learning-based Obstacle Avoidance for Robot Movement in Warehouse Environments](https://mlsanity.com/paper/2409.14972/) (2024)
- [AR Overlay: Training Image Pose Estimation on Curved Surface in a Synthetic Way](https://mlsanity.com/paper/2409.14577/) (2024)
- [Graphical Structural Learning of rs-fMRI data in Heavy Smokers](https://mlsanity.com/paper/2409.08395/) (2024)
- [EITNet: An IoT-Enhanced Framework for Real-Time Basketball Action Recognition](https://mlsanity.com/paper/2410.09954/) (2024)
- [Predicting 30-Day Hospital Readmission in Medicare Patients: Insights from an LSTM Deep Learning Model](https://mlsanity.com/paper/2410.17545/) (2024)
- [Real-time Monitoring of Lower Limb Movement Resistance Based on Deep Learning](https://mlsanity.com/paper/2410.19769/) (2024)
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- [Real-time Monitoring and Analysis of Track and Field Athletes Based on Edge Computing and Deep Reinforcement Learning Algorithm](https://mlsanity.com/paper/2411.06720/) (2024)
- [IoT-Based 3D Pose Estimation and Motion Optimization for Athletes: Application of C3D and OpenPose](https://mlsanity.com/paper/2411.12676/) (2024)
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- [GTA-Net: An IoT-Integrated 3D Human Pose Estimation System for Real-Time Adolescent Sports Posture Correction](https://mlsanity.com/paper/2411.06725/) (2024)
- [Optimized CNNs for Rapid 3D Point Cloud Object Recognition](https://mlsanity.com/paper/2412.02855/) (2024)
- [Enhancing Exchange Rate Forecasting with Explainable Deep Learning Models](https://mlsanity.com/paper/2410.19241/) (2024)
- [Construction and optimization of health behavior prediction model for the elderly in smart elderly care](https://mlsanity.com/paper/2412.02062/) (2024)
- [Cardiovascular Disease Detection By Leveraging Semi-Supervised Learning](https://mlsanity.com/paper/2412.10567/) (2024)

## 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.