Cover Image

Association between nutritional factors, inflammatory biomarkers and cancer types: an analysis of NHANES data using machine learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Yuqing, Zhao, Meng, Hu, Guanlan, Zhang, Yuchen
Format:	Preprint
Published:	2025
Subjects:	Quantitative Methods Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

NHANES-GCP: Leveraging the Google Cloud Platform and BigQuery ML for reproducible machine learning with data from the National Health and Nutrition Examination Survey
by: Katz, B. Ross, et al.
Published: (2024)

Associations between exposure to OPEs and rheumatoid arthritis risk among adults in NHANES, 2011-2018
by: Singh, Sneha, et al.
Published: (2024)

Reliable algorithm selection for machine learning-guided design
by: Fannjiang, Clara, et al.
Published: (2025)

Pathology-genomic fusion via biologically informed cross-modality graph learning for survival analysis
by: Zhang, Zeyu, et al.
Published: (2024)

Association between Sitting Time and Urinary Incontinence in the US Population: data from the National Health and Nutrition Examination Survey (NHANES) 2007 to 2018
by: Wang, Guanbo, et al.
Published: (2024)

Nonparametric learning of covariate-based Markov jump processes using RKHS techniques
by: Han, Yuchen, et al.
Published: (2025)

dsLassoCov: a federated machine learning approach incorporating covariate control
by: Cao, Han, et al.
Published: (2024)

Estimating carbon pools in the shelf sea environment: reanalysis or model-informed machine learning?
by: Skakala, Jozef
Published: (2025)

DeepLINK-T: deep learning inference for time series data using knockoffs and LSTM
by: Zuo, Wenxuan, et al.
Published: (2024)

Nondestructive, quantitative viability analysis of 3D tissue cultures using machine learning image segmentation
by: Trettner, Kylie J., et al.
Published: (2023)

SSRCA: a novel machine learning pipeline to perform sensitivity analysis for agent-based models
by: Rohr, Edward H., et al.
Published: (2025)

Association of normalization, non-differentially expressed genes and data source with machine learning performance in intra-dataset or cross-dataset modelling of transcriptomic and clinical data
by: Deng, Fei, et al.
Published: (2025)

Persistent reachability homology in machine learning applications
by: Caputi, Luigi, et al.
Published: (2025)

Learning to learn ecosystems from limited data -- a meta-learning approach
by: Zhai, Zheng-Meng, et al.
Published: (2024)

Learning surrogate equations for the analysis of an agent-based cancer model
by: Burrage, Kevin, et al.
Published: (2025)

eegFloss: A Python package for refining sleep EEG recordings using machine learning models
by: Sikder, Niloy, et al.
Published: (2025)

Exploring proteomic signatures in sepsis and non-infectious systemic inflammatory response syndrome
by: Ruiz-Sanmartín, Adolfo, et al.
Published: (2025)

A Protocol to Exposure Path Analysis for Multiple Stressors Associated with Cardiovascular Disease Risk: A Novel Approach Using NHANES Data
by: Liu, Jiangling, et al.
Published: (2025)

Predicting microsatellite instability and key biomarkers in colorectal cancer from H&E-stained images: Achieving SOTA predictive performance with fewer data using Swin Transformer
by: Guo, Bangwei, et al.
Published: (2022)

Assessing global drivers of forest transpiration using clustered machine learning models
by: Thornwell, Morgan, et al.
Published: (2026)

Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only data
by: Frank, Robert, et al.
Published: (2025)

Can machine learning predict citizen-reported angler behavior?
by: Schmid, Julia S., et al.
Published: (2024)

The CausalBench challenge: A machine learning contest for gene network inference from single-cell perturbation data
by: Chevalley, Mathieu, et al.
Published: (2023)

epiGPTope: A machine learning-based epitope generator and classifier
by: Manrique, Natalia Flechas, et al.
Published: (2025)

Multi-layer matrix factorization for cancer subtyping using full and partial multi-omics dataset
by: Ren, Yingxuan, et al.
Published: (2024)

Prediction of cancer dynamics under treatment using Bayesian neural networks: A simulated study
by: Myklebust, Even Moa, et al.
Published: (2024)

An inferential measure of dependence between two systems using Bayesian model comparison
by: Marrelec, Guillaume, et al.
Published: (2024)

Combining machine learning with data assimilation to improve the quality of phytoplankton forecasting in a shelf sea environment
by: Banerjee, Deep S, et al.
Published: (2025)

Machine learning algorithms to predict stroke in China based on causal inference of time series analysis
by: Zheng, Qizhi, et al.
Published: (2025)

Dual-stage optimizer for systematic overestimation adjustment applied to multi-objective genetic algorithms for biomarker selection
by: Cattelani, Luca, et al.
Published: (2023)

Federated attention consistent learning models for prostate cancer diagnosis and Gleason grading
by: Kong, Fei, et al.
Published: (2023)

Using machine learning to inform harvest control rule design in complex fishery settings
by: Montealegre-Mora, Felipe, et al.
Published: (2024)

Zero-Shot Learning with Subsequence Reordering Pretraining for Compound-Protein Interaction
by: Zhang, Hongzhi, et al.
Published: (2025)

Digitally enriching a screening population for pancreatic cancer using routine blood-based measures and clinical histories
by: Varghese, Chris, et al.
Published: (2026)

SpanSeq: Similarity-based sequence data splitting method for improved development and assessment of deep learning projects
by: Florensa, Alfred Ferrer, et al.
Published: (2024)

Motif-aware Attribute Masking for Molecular Graph Pre-training
by: Inae, Eric, et al.
Published: (2023)

DeepDR: an integrated deep-learning model web server for drug repositioning
by: Jin, Shuting, et al.
Published: (2025)

BEACON: Benchmark for Comprehensive RNA Tasks and Language Models
by: Ren, Yuchen, et al.
Published: (2024)

Accurate RNA 3D structure prediction using a language model-based deep learning approach
by: Shen, Tao, et al.
Published: (2022)

Automating proton PBS treatment planning for head and neck cancers using policy gradient-based deep reinforcement learning
by: Wang, Qingqing, et al.
Published: (2024)