Cargando…

Efficacy and Safety of Anticoagulation Treatment in COVID-19 Patient Subgroups Identified by Clinical-Based Stratification and Unsupervised Machine Learning: A Matched Cohort Study

Objective: To explore the efficacy of anticoagulation in improving outcomes and safety of Coronavirus disease 2019 (COVID-19) patients in subgroups identified by clinical-based stratification and unsupervised machine learning. Methods: This single-center retrospective cohort study unselectively revi...

Descripción completa

Detalles Bibliográficos
Autores principales:	Bian, Yi, Le, Yue, Du, Han, Chen, Junfang, Zhang, Ping, He, Zhigang, Wang, Ye, Yu, Shanshan, Fang, Yu, Yu, Gang, Ling, Jianmin, Feng, Yikuan, Wei, Sheng, Huang, Jiao, Xiao, Liuniu, Zheng, Yingfang, Yu, Zhen, Li, Shusheng
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2021
Materias:	Medicine
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740912/ https://www.ncbi.nlm.nih.gov/pubmed/35004751 http://dx.doi.org/10.3389/fmed.2021.786414

Ejemplares similares

The modified NUTRIC score can be used for nutritional risk assessment as well as prognosis prediction in critically ill COVID-19 patients
por: Zhang, Ping, et al.
Publicado: (2021)

Microbiome Features Differentiating Unsupervised-Stratification-Based Clusters of Patients with Abnormal Glycometabolism
por: Xu, Ting, et al.
Publicado: (2023)

Identifying novel subgroups in heart failure patients with unsupervised machine learning: A scoping review
por: Sun, Jin, et al.
Publicado: (2022)

Unsupervised data-driven stratification of mentalizing heterogeneity in autism
por: Lombardo, Michael V., et al.
Publicado: (2016)

Unsupervised neurobiology-driven stratification of clinical heterogeneity in depression
por: Colombo, F., et al.
Publicado: (2023)

Serum creatine kinase levels are not associated with an increased need for continuous renal replacement therapy in patients with acute kidney injury following rhabdomyolysis
por: Xiao, Liuniu, et al.
Publicado: (2022)

Unsupervised Learning for Automated Detection of Coronary Artery Disease Subgroups
por: Flores, Alyssa M., et al.
Publicado: (2021)

Unsupervised machine learning improves risk stratification in newly diagnosed multiple myeloma: an analysis of the Spanish Myeloma Group
por: Mosquera Orgueira, Adrian, et al.
Publicado: (2022)

Stratification of multiple sclerosis patients using unsupervised machine learning: a single-visit MRI-driven approach
por: Pontillo, Giuseppe, et al.
Publicado: (2022)

Prognostic stratification of molecularly and clinically distinct subgroup in children with acute monocytic leukemia
por: Liu, Li‐Peng, et al.
Publicado: (2020)

Poster 179: Unsupervised Machine Learning to Identify Clinically Meaningful Subgroups in Patients Undergoing Arthroscopic Rotator Cuff Repair
por: Lu, Yining, et al.
Publicado: (2023)

Comparison of Unsupervised Machine Learning Approaches for Cluster Analysis to Define Subgroups of Heart Failure with Preserved Ejection Fraction with Different Outcomes
por: Nouraei, Hirmand, et al.
Publicado: (2022)

Risk stratification in clinical trials: a subgroup to be encouraged
por: Clayton, Tim, et al.
Publicado: (2013)

Unsupervised Learning Applied to the Stratification of Preterm Birth Risk in Brazil with Socioeconomic Data
por: Lopes, Márcio L. B., et al.
Publicado: (2022)

Using Unsupervised Machine Learning to Identify Age- and Sex-Independent Severity Subgroups Among Patients with COVID-19: Observational Longitudinal Study
por: Benito-León, Julián, et al.
Publicado: (2021)

Unsupervised machine learning using K-means identifies radiomic subgroups of pediatric low-grade gliomas that correlate with key molecular markers
por: Haldar, Debanjan, et al.
Publicado: (2022)

Unsupervised Machine Learning Applied to Seismic Interpretation: Towards an Unsupervised Automated Interpretation Tool
por: Celecia, Alimed, et al.
Publicado: (2021)

Machine Learning in Causal Inference: Application in Pharmacovigilance
por: Zhao, Yiqing, et al.
Publicado: (2022)

Melatonin Attenuates Sepsis-Induced Acute Lung Injury via Inhibiting Excessive Mitophagy
por: Ling, Jianmin, et al.
Publicado: (2023)

Immunophenotypes Based on the Tumor Immune Microenvironment Allow for Unsupervised Penile Cancer Patient Stratification
por: Chu, Chengbiao, et al.
Publicado: (2020)

Conserved transcriptomic profile between mouse and human colitis allows unsupervised patient stratification
por: Czarnewski, Paulo, et al.
Publicado: (2019)

Correction to: Machine Learning in Causal Inference: Application in Pharmacovigilance
por: Zhao, Yiqing, et al.
Publicado: (2022)

Matching sensor ontologies with unsupervised neural network with competitive learning
por: Xue, Xingsi, et al.
Publicado: (2021)

Unsupervised Adaptation of Brain-Machine Interface Decoders
por: Gürel, Tayfun, et al.
Publicado: (2012)

Unsupervised Machine Learning to Identify Depressive Subtypes
por: Kung, Benson, et al.
Publicado: (2022)

Unsupervised machine learning based on clinical factors for the detection of coronary artery atherosclerosis in type 2 diabetes mellitus
por: Jiang, Yu, et al.
Publicado: (2022)

Unsupervised cluster analysis reveals distinct subgroups in healthy population with different exercise responses of cardiorespiratory fitness
por: Xie, Lin, et al.
Publicado: (2023)

Semi-supervised and unsupervised machine learning: novel strategies
por: Albalate, Amparo, et al.
Publicado: (2011)

Keratoconus severity identification using unsupervised machine learning
por: Yousefi, Siamak, et al.
Publicado: (2018)

Recreation of the periodic table with an unsupervised machine learning algorithm
por: Kusaba, Minoru, et al.
Publicado: (2021)

Observing flow of He II with unsupervised machine learning
por: Wen, X., et al.
Publicado: (2022)

Unsupervised machine learning discovers classes in aluminium alloys
por: Bhat, Ninad, et al.
Publicado: (2023)

Handling DNA malfunctions by unsupervised machine learning model
por: Khazaaleh, Mutaz Kh., et al.
Publicado: (2023)

Using Bayesian-PBPK modeling for assessment of inter-individual variability and subgroup stratification
por: Krauss, Markus, et al.
Publicado: (2013)

Construct validity of the OCTOPuS stratification algorithm for allocating patients with knee osteoarthritis into subgroups
por: Knoop, Jesper, et al.
Publicado: (2021)

Stratification or Polarization: a Qualitative Study of the Formation of Status-Based Subgroups in China
por: Zhang, Yue, et al.
Publicado: (2022)

Subgrouping patients with sciatica in primary care for matched care pathways: development of a subgrouping algorithm
por: Konstantinou, Kika, et al.
Publicado: (2019)

Public perception on 'healthy ageing' in the past decade: An unsupervised machine learning of 63,809 Twitter posts
por: Ng, Qin Xiang, et al.
Publicado: (2023)

An Unsupervised Deep Hyperspectral Anomaly Detector
por: Ma, Ning, et al.
Publicado: (2018)

Unsupervised analysis reveals two molecular subgroups of serous ovarian cancer with distinct gene expression profiles and survival
por: Lisowska, Katarzyna M., et al.
Publicado: (2016)

Cannot write session to /tmp/vufind_sessions/sess_8bj9226muoehg2lj6mt532pd82