Imagen de Portada

Deep learning outperforms traditional machine learning methods in predicting childhood malnutrition: evidence from survey data

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Bastola, Deepak, Li, Yang
Formato:	Preprint
Publicado:	2026
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Hybrid Topic-Semantic Labeling and Graph Embeddings for Unsupervised Legal Document Clustering
por: Bastola, Deepak, et al.
Publicado: (2025)

Predicting Anemia Among Under-Five Children in Nepal Using Machine Learning and Deep Learning
por: Bastola, Deepak, et al.
Publicado: (2026)

Using ensemble methods of machine learning to predict real estate prices
por: Pastukh, Oleh, et al.
Publicado: (2025)

Using machine learning methods to predict cognitive age from psychophysiological tests
por: Tyurina, Daria D., et al.
Publicado: (2025)

Early evidence of how LLMs outperform traditional systems on OCR/HTR tasks for historical records
por: Kim, Seorin, et al.
Publicado: (2025)

FuXi-S2S: A machine learning model that outperforms conventional global subseasonal forecast models
por: Chen, Lei, et al.
Publicado: (2023)

Stability of clinical prediction models developed using statistical or machine learning methods
por: Riley, Richard D, et al.
Publicado: (2022)

Causal machine learning for predicting treatment outcomes
por: Feuerriegel, Stefan, et al.
Publicado: (2024)

A survey and taxonomy of loss functions in machine learning
por: Ciampiconi, Lorenzo, et al.
Publicado: (2023)

A machine learning model for skillful climate system prediction
por: Zhou, Chenguang, et al.
Publicado: (2025)

A step towards the integration of machine learning and classic model-based survey methods
por: Żądło, Tomasz, et al.
Publicado: (2024)

Enhanced prediction of spine surgery outcomes using advanced machine learning techniques and oversampling methods
por: Benítez-Andrades, José Alberto, et al.
Publicado: (2025)

Benchmarking machine learning models for predicting aerofoil performance
por: Summerell, Oliver, et al.
Publicado: (2025)

A review of predictive uncertainty estimation with machine learning
por: Tyralis, Hristos, et al.
Publicado: (2022)

Comparison of gait phase detection using traditional machine learning and deep learning techniques
por: Nazari, Farhad, et al.
Publicado: (2024)

Text classification using machine learning methods
por: Oancea, Bogdan
Publicado: (2025)

Meshless method stencil evaluation with machine learning
por: Rot, Miha, et al.
Publicado: (2022)

Deep learning for predicting the occurrence of tipping points
por: Zhuge, Chengzuo, et al.
Publicado: (2024)

Applications of machine learning to predict seasonal precipitation for East Africa
por: Scheuerer, Michael, et al.
Publicado: (2024)

A comparative study of conformal prediction methods for valid uncertainty quantification in machine learning
por: Dewolf, Nicolas
Publicado: (2024)

Uncertainty estimation of machine learning spatial precipitation predictions from satellite data
por: Papacharalampous, Georgia, et al.
Publicado: (2023)

On the use of adversarial validation for quantifying dissimilarity in geospatial machine learning prediction
por: Wang, Yanwen, et al.
Publicado: (2024)

Gas trap prediction from 3D seismic and well test data using machine learning
por: Ivlev, Dmitry
Publicado: (2024)

Physics-based machine learning framework for predicting NOx emissions from compression ignition engines using on-board diagnostics data
por: Selvam, Harish Panneer, et al.
Publicado: (2025)

Downscaling human mobility data based on demographic socioeconomic and commuting characteristics using interpretable machine learning methods
por: Jiang, Yuqin, et al.
Publicado: (2025)

A deep learning and machine learning approach to predict neonatal death in the context of São Paulo
por: Raihan, Mohon, et al.
Publicado: (2025)

Accelerating the prediction of inorganic surfaces with machine learning interatomic potentials
por: Noordhoek, Kyle, et al.
Publicado: (2023)

Integrating behavior analysis with machine learning to predict online learning performance: A scientometric review and empirical study
por: Yuan, Jin, et al.
Publicado: (2024)

Assessment of machine learning methods for state-to-state approaches
por: Campoli, Lorenzo, et al.
Publicado: (2021)

Machine learning and machine learned prediction in chest X-ray images
por: Garrett, Shereiff, et al.
Publicado: (2025)

Quality analysis and evaluation prediction of RAG retrieval based on machine learning algorithms
por: Zhang, Ruoxin, et al.
Publicado: (2025)

An efficient, accurate, and interpretable machine learning method for computing probability of failure
por: Zhu, Jacob, et al.
Publicado: (2026)

A parsimonious, computationally efficient machine learning method for spatial regression
por: Žukovič, Milan, et al.
Publicado: (2023)

Feasibility of machine learning-based rice yield prediction in India at the district level using climate reanalysis data
por: De Clercq, Djavan, et al.
Publicado: (2024)

Survival modeling using deep learning, machine learning and statistical methods: A comparative analysis for predicting mortality after hospital admission
por: Wang, Ziwen, et al.
Publicado: (2024)

Multimodal machine learning with large language embedding model for polymer property prediction
por: Zhang, Tianren, et al.
Publicado: (2025)

Learning from the past: predicting critical transitions with machine learning trained on surrogates of historical data
por: Ma, Zhiqin, et al.
Publicado: (2024)

Arnoldi Singular Vector perturbations for machine learning weather prediction
por: Winkler, Jens, et al.
Publicado: (2025)

Comparison of deep learning and conventional methods for disease onset prediction
por: John, Luis H., et al.
Publicado: (2024)

Epidemic outbreak prediction using machine learning models
por: Pramod, Akshara, et al.
Publicado: (2023)