Cargando…

Comprehensive Analysis of Clinical Logistic and Machine Learning-Based Models for the Evaluation of Pulmonary Nodules

INTRODUCTION: Over the years, multiple models have been developed for the evaluation of pulmonary nodules (PNs). This study aimed to comprehensively investigate clinical models for estimating the malignancy probability in patients with PNs. METHODS: PubMed, EMBASE, Cochrane Library, and Web of Scien...

Descripción completa

Detalles Bibliográficos
Autores principales:	Zhang, Kai, Wei, Zihan, Nie, Yuntao, Shen, Haifeng, Wang, Xin, Wang, Jun, Yang, Fan, Chen, Kezhong
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Elsevier 2022
Materias:	Original Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8980995/ https://www.ncbi.nlm.nih.gov/pubmed/35392654 http://dx.doi.org/10.1016/j.jtocrr.2022.100299

Ejemplares similares

Molecular Alterations in Lung Adenocarcinoma With Ground-Glass Nodules: A Systematic Review and Meta-Analysis
por: Wei, Zihan, et al.
Publicado: (2021)

Comparison of Clinical and Pathological Characteristics Between Extremely Multiple GGNs and Single GGNs
por: Wang, Xin, et al.
Publicado: (2021)

Putting artificial intelligence (AI) on the spot: machine learning evaluation of pulmonary nodules
por: Tandon, Yasmeen K., et al.
Publicado: (2020)

Prediction model for malignant pulmonary nodules based on cfMeDIP‐seq and machine learning
por: Qi, Jian, et al.
Publicado: (2021)

Comprehensive Logistics
por: Gudehus, Timm, et al.
Publicado: (2012)

Logistic Regression for Machine Learning in Process Tomography
por: Rymarczyk, Tomasz, et al.
Publicado: (2019)

Logistics Finance Collaborative Development Model Based on Machine Learning
por: Wang, Yuqin
Publicado: (2022)

CT and CEA‐based machine learning model for predicting malignant pulmonary nodules
por: Liu, Man, et al.
Publicado: (2022)

Machine learning logistics: model management in the real world
por: Dunning, Ted, et al.
Publicado: (2017)

Potential clinical utility of liquid biopsy in early-stage non-small cell lung cancer
por: Shen, Haifeng, et al.
Publicado: (2022)

Prediction of epidemic trends in COVID-19 with logistic model and machine learning technics
por: Wang, Peipei, et al.
Publicado: (2020)

Comparison of Conventional Logistic Regression and Machine Learning Methods for Predicting Delayed Cerebral Ischemia After Aneurysmal Subarachnoid Hemorrhage: A Multicentric Observational Cohort Study
por: Hu, Ping, et al.
Publicado: (2022)

Pulmonary Nodule Recognition Based on Multiple Kernel Learning Support Vector Machine-PSO
por: Li, Yang, et al.
Publicado: (2018)

Evaluation System of Smart Logistics Comprehensive Management Based on Hospital Data Fusion Technology
por: Yao, Biwen, et al.
Publicado: (2022)

Influencing factor modeled examination on internet rural logistics talent innovation mechanism based on fuzzy comprehensive evaluation method
por: Zhan, Hui, et al.
Publicado: (2021)

Predicting Type 2 Diabetes Using Logistic Regression and Machine Learning Approaches
por: Joshi, Ram D., et al.
Publicado: (2021)

Prediction of preterm birth in nulliparous women using logistic regression and machine learning
por: Arabi Belaghi, Reza, et al.
Publicado: (2021)

Logistic Regression With Machine Learning Sheds Light on the Problematic Sexual Behavior Phenotype
por: Jiang, Shui, et al.
Publicado: (2023)

Reliability and Clinical Utility of Machine Learning to Predict Stroke Prognosis: Comparison with Logistic Regression
por: Jang, Su-Kyeong, et al.
Publicado: (2020)

Optical coherence tomography for identification of malignant pulmonary nodules based on random forest machine learning algorithm
por: Ding, Ming, et al.
Publicado: (2021)

Machine Learning: An Approach in Identifying Risk Factors for Coercion Compared to Binary Logistic Regression
por: Hotzy, Florian, et al.
Publicado: (2018)

Don’t dismiss logistic regression: the case for sensible extraction of interactions in the era of machine learning
por: Levy, Joshua J., et al.
Publicado: (2020)

Delirium misdiagnosis risk in psychiatry: a machine learning-logistic regression predictive algorithm
por: Hercus, Catherine, et al.
Publicado: (2020)

Research on Intelligent Warehousing and Logistics Management System of Electronic Market Based on Machine Learning
por: Zhang, Ruifeng, et al.
Publicado: (2022)

An Application of Machine Learning to Logistics Performance Prediction: An Economics Attribute-Based of Collective Instance
por: Jomthanachai, Suriyan, et al.
Publicado: (2023)

Comparison of machine learning and logistic regression as predictive models for adverse maternal and neonatal outcomes of preeclampsia: A retrospective study
por: Zheng, Dongying, et al.
Publicado: (2022)

Automatic Pulmonary Nodule Detection Applying Deep Learning or Machine Learning Algorithms to the LIDC-IDRI Database: A Systematic Review
por: Pehrson, Lea Marie, et al.
Publicado: (2019)

Deep learning-based growth prediction for sub-solid pulmonary nodules on CT images
por: Liao, Ri-qiang, et al.
Publicado: (2022)

Comprehensive Evaluation and Comparison of Machine Learning Methods in QSAR Modeling of Antioxidant Tripeptides
por: Du, Zhenjiao, et al.
Publicado: (2022)

Generative and reproducible benchmarks or comprehensive evaluation machine learning classifiers
por: Orzechowski, Patryk, et al.
Publicado: (2022)

PET/CT in the evaluation of pulmonary solitary nodule
por: Barbosa, Felipe de Galiza
Publicado: (2016)

Machine Learning-Based Modeling of Ovarian Response and the Quantitative Evaluation of Comprehensive Impact Features
por: Liu, Liu, et al.
Publicado: (2022)

Novel Method of Classification in Knee Osteoarthritis: Machine Learning Application Versus Logistic Regression Model
por: Yang, Jung Ho, et al.
Publicado: (2020)

Retraction: Tracking COVID-19 vaccine hesitancy and logistical challenges: A machine learning approach
por: Dutta, Shantanu, et al.
Publicado: (2021)

Machine learning did not beat logistic regression in time series prediction for severe asthma exacerbations
por: de Hond, Anne A. H., et al.
Publicado: (2022)

Predicting Malignancy and Invasiveness of Pulmonary Subsolid Nodules on CT Images Using Deep Learning
por: Shen, Tianle, et al.
Publicado: (2021)

Risk prediction for malignant intraductal papillary mucinous neoplasm of the pancreas: logistic regression versus machine learning
por: Kang, Jae Seung, et al.
Publicado: (2020)

Status Forecasting Based on the Baseline Information Using Logistic Regresssion
por: Zhao, Xin, et al.
Publicado: (2022)

Calculus of thought: neuromorphic logistic regression in cognitive machines
por: Rice, Daniel M
Publicado: (2014)

The logic of logistics: theory, algorithms, and applications for logistics management
por: Simchi-Levi, David, et al.
Publicado: (2014)

Cannot write session to /tmp/vufind_sessions/sess_r845i0f418uf7isrnbar3no1ku