Cargando…

Benchmarking AutoML frameworks for disease prediction using medical claims

OBJECTIVES: Ascertain and compare the performances of Automated Machine Learning (AutoML) tools on large, highly imbalanced healthcare datasets. MATERIALS AND METHODS: We generated a large dataset using historical de-identified administrative claims including demographic information and flags for di...

Descripción completa

Detalles Bibliográficos
Autores principales:	A. Romero, Roland Albert, Y. Deypalan, Mariefel Nicole, Mehrotra, Suchit, Jungao, John Titus, Sheils, Natalie E., Manduchi, Elisabetta, Moore, Jason H.
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2022
Materias:	Short Report
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9327416/ https://www.ncbi.nlm.nih.gov/pubmed/35883154 http://dx.doi.org/10.1186/s13040-022-00300-2

Ejemplares similares

AutoML for Fast Simulation
por: Nascimento Ferreira, Poliana
Publicado: (2021)

Landslide Susceptibility Assessment Using an AutoML Framework
por: Bruzón, Adrián G., et al.
Publicado: (2021)

Benchmarking AutoML for regression tasks on small tabular data in materials design
por: Conrad, Felix, et al.
Publicado: (2022)

Review of ML and AutoML Solutions to Forecast Time-Series Data
por: Alsharef, Ahmad, et al.
Publicado: (2022)

An improved hyperparameter optimization framework for AutoML systems using evolutionary algorithms
por: Vincent, Amala Mary, et al.
Publicado: (2023)

Net-Net Auto Machine Learning (AutoML) Prediction of Complex Ecosystems
por: Barreiro, Enrique, et al.
Publicado: (2018)

Optimization of running-in surface morphology parameters based on the AutoML model
por: Ge, Guangyuan, et al.
Publicado: (2021)

BACS: blockchain and AutoML-based technology for efficient credit scoring classification
por: Yang, Fan, et al.
Publicado: (2022)

Hierarchical automated machine learning (AutoML) for advanced unconventional reservoir characterization
por: Mubarak, Yousef, et al.
Publicado: (2023)

Automated Prediction of Crack Propagation Using H2O AutoML
por: Omar, Intisar, et al.
Publicado: (2023)

A Bibliometric Analysis and Benchmark of Machine Learning and AutoML in Crash Severity Prediction: The Case Study of Three Colombian Cities
por: Angarita-Zapata, Juan S., et al.
Publicado: (2021)

Micro-architecture design exploration template for AutoML case study on SqueezeSEMAuto
por: Chantrapornchai, Chantana, et al.
Publicado: (2023)

RETRACTED ARTICLE: Modeling the progression of COVID-19 deaths using Kalman Filter and AutoML
por: Han, Tao, et al.
Publicado: (2021)

Optimization of Deep Architectures for EEG Signal Classification: An AutoML Approach Using Evolutionary Algorithms
por: Aquino-Brítez, Diego, et al.
Publicado: (2021)

Curated Database and Preliminary AutoML QSAR Model for 5-HT1A Receptor
por: Czub, Natalia, et al.
Publicado: (2021)

Human behavior in image-based Road Health Inspection Systems despite the emerging AutoML
por: Siriborvornratanakul, Thitirat
Publicado: (2022)

Retraction Note: Modeling the progression of COVID-19 deaths using Kalman Filter and AutoML
por: Han, Tao, et al.
Publicado: (2023)

AutoML accurately predicts endovascular mechanical thrombectomy in acute large vessel ischemic stroke
por: Raj, Rishi, et al.
Publicado: (2023)

Author Correction: Hierarchical automated machine learning (AutoML) for advanced unconventional reservoir characterization
por: Mubarak, Yousef, et al.
Publicado: (2023)

Automated machine learning and explainable AI (AutoML-XAI) for metabolomics: improving cancer diagnostics
por: Bifarin, Olatomiwa O., et al.
Publicado: (2023)

AutoML-ID: automated machine learning model for intrusion detection using wireless sensor network
por: Singh, Abhilash, et al.
Publicado: (2022)

Automated machine learning (AutoML) can predict 90-day mortality after gastrectomy for cancer
por: SenthilKumar, Gopika, et al.
Publicado: (2023)

Pharm‐AutoML: An open‐source, end‐to‐end automated machine learning package for clinical outcome prediction
por: Liu, Gengbo, et al.
Publicado: (2021)

Comparisons of automated machine learning (AutoML) in predicting whistleblowing of academic dishonesty with demographic and theory of planned behavior
por: Rahman, Rahayu Abdul, et al.
Publicado: (2023)

Hyperparameter Tuning and Pipeline Optimization via Grid Search Method and Tree-Based AutoML in Breast Cancer Prediction
por: Radzi, Siti Fairuz Mat, et al.
Publicado: (2021)

SCP4ssd: A Serverless Platform for Nucleotide Sequence Synthesis Difficulty Prediction Using an AutoML Model
por: Zhang, Jianqi, et al.
Publicado: (2023)

Machine learning approach in predicting GlutoPeak test parameters from image data with AutoML and transfer learning
por: Murai, Takehiro, et al.
Publicado: (2023)

Hands-on automated machine learning: a beginner's guide to building automated machine learning systems using AutoML and Python
por: Das, Sibanjan, et al.
Publicado: (2018)

Automated Curation of CNMF-E-Extracted ROI Spatial Footprints and Calcium Traces Using Open-Source AutoML Tools
por: Tran, Lina M., et al.
Publicado: (2020)

Automated Machine Learning (AutoML)-Derived Preconception Predictive Risk Model to Guide Early Intervention for Gestational Diabetes Mellitus
por: Kumar, Mukkesh, et al.
Publicado: (2022)

Machine Learning Models for Slope Stability Classification of Circular Mode Failure: An Updated Database and Automated Machine Learning (AutoML) Approach
por: Ma, Junwei, et al.
Publicado: (2022)

Comparison of pre-trained language models in terms of carbon emissions, time and accuracy in multi-label text classification using AutoML
por: Savci, Pinar, et al.
Publicado: (2023)

Do AutoML-Based QSAR Models Fulfill OECD Principles for Regulatory Assessment? A 5-HT(1A) Receptor Case
por: Czub, Natalia, et al.
Publicado: (2022)

Research and Application Validation of a Feature Wavelength Selection Method Based on Acousto-Optic Tunable Filter (AOTF) and Automatic Machine Learning (AutoML)
por: Ji, Zhongpeng, et al.
Publicado: (2022)

Open-source FPGA-ML codesign for the MLPerf Tiny Benchmark
por: Borras, Hendrik, et al.
Publicado: (2022)

Benchmarking variational AutoEncoders on cancer transcriptomics data
por: Eltager, Mostafa, et al.
Publicado: (2023)

Testing the applicability and performance of Auto ML for potential applications in diagnostic neuroradiology
por: Musigmann, Manfred, et al.
Publicado: (2022)

BioAutoML: automated feature engineering and metalearning to predict noncoding RNAs in bacteria
por: Bonidia, Robson P, et al.
Publicado: (2022)

Leveraging Automated Machine Learning for the Analysis of Global Public Health Data: A Case Study in Malaria
por: Manduchi, Elisabetta, et al.
Publicado: (2021)

DroidAutoML: A Microservice Architecture to Automate the Evaluation of Android Machine Learning Detection Systems
por: Bromberg, Yérom-David, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_t1b9k0394jan1gs7s9jfidl290