Cargando…

Causal discovery approach with reinforcement learning for risk factors of type II diabetes mellitus

BACKGROUND: Statistical correlation analysis is currently the most typically used approach for investigating the risk factors of type 2 diabetes mellitus (T2DM). However, this approach does not readily reveal the causal relationships between risk factors and rarely describes the causal relationships...

Descripción completa

Detalles Bibliográficos
Autores principales:	Gao, Xiu-E., Hu, Jian-Gang, Chen, Bo, Wang, Yun-Ming, zhou, Sheng-Bin
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2023
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10362703/ https://www.ncbi.nlm.nih.gov/pubmed/37480046 http://dx.doi.org/10.1186/s12859-023-05405-x

Ejemplares similares

Improved Functional Causal Likelihood-Based Causal Discovery Method for Diabetes Risk Factors
por: Gao, Xiue, et al.
Publicado: (2021)

The Importance of Discovery in Children's Causal Learning from Interventions
por: Sobel, David M., et al.
Publicado: (2010)

Incorporating causal factors into reinforcement learning for dynamic treatment regimes in HIV
por: Yu, Chao, et al.
Publicado: (2019)

The rational use of causal inference to guide reinforcement learning strengthens with age
por: Cohen, Alexandra O., et al.
Publicado: (2020)

A Complex Systems Approach to Causal Discovery in Psychiatry
por: Saxe, Glenn N., et al.
Publicado: (2016)

Causal discovery for the microbiome
por: Corander, Jukka, et al.
Publicado: (2022)

A novel method for causal structure discovery from EHR data and its application to type-2 diabetes mellitus
por: Shen, Xinpeng, et al.
Publicado: (2021)

Generalism drives abundance: A computational causal discovery approach
por: Song, Chuliang, et al.
Publicado: (2022)

An Evaluation of Active Learning Causal Discovery Methods for Reverse-Engineering Local Causal Pathways of Gene Regulation
por: Ma, Sisi, et al.
Publicado: (2016)

Causality relationships between coagulation factors in type 2 diabetes mellitus: path analysis approach
por: Dayer, Mohammad Reza, et al.
Publicado: (2014)

Statistical methods for dynamic treatment regimes: reinforcement learning, causal inference, and personalized medicine
por: Chakraborty, Bibhas, et al.
Publicado: (2013)

CausalMGM: an interactive web-based causal discovery tool
por: Ge, Xiaoyu, et al.
Publicado: (2020)

From Semantics to Execution: Integrating Action Planning With Reinforcement Learning for Robotic Causal Problem-Solving
por: Eppe, Manfred, et al.
Publicado: (2019)

Applying causal discovery to single-cell analyses using CausalCell
por: Wen, Yujian, et al.
Publicado: (2023)

A reinforcement learning approach to gait training improves retention
por: Hasson, Christopher J., et al.
Publicado: (2015)

Reinforcement Learning Approaches in Social Robotics
por: Akalin, Neziha, et al.
Publicado: (2021)

Towards efficient discovery of green synthetic pathways with Monte Carlo tree search and reinforcement learning
por: Wang, Xiaoxue, et al.
Publicado: (2020)

Statistical reinforcement learning: modern machine learning approaches
por: Sugiyama, Masashi
Publicado: (2015)

Mental health progress requires causal diagnostic nosology and scalable causal discovery
por: Saxe, Glenn N., et al.
Publicado: (2022)

Pruning the Communication Bandwidth between Reinforcement Learning Agents through Causal Inference: An Innovative Approach to Designing a Smart Grid Power System
por: Zhang, Xianjie, et al.
Publicado: (2022)

Causality Is an Effect, II
por: Schulman, Lawrence S.
Publicado: (2021)

Diabetes mellitus tipo II
por: Potenciano Lizcano, Andrea
Publicado: (1994)

Discovery of Causal Paths in Cardiorespiratory Parameters: A Time-Independent Approach in Elite Athletes
por: Młyńczak, Marcel, et al.
Publicado: (2018)

Benchmarking of Data-Driven Causality Discovery Approaches in the Interactions of Arctic Sea Ice and Atmosphere
por: Huang, Yiyi, et al.
Publicado: (2021)

Constraint-based causal discovery with mixed data
por: Tsagris, Michail, et al.
Publicado: (2018)

Aristotle: stratified causal discovery for omics data
por: Mansouri, Mehrdad, et al.
Publicado: (2022)

Are diabetes mellitus and lipoprotein(a) independently or causally associated with an increased cardiovascular risk?
por: Vavlukis, Marija
Publicado: (2017)

Reinforcement learning approach for fast qubit control
por: Ustyuzhanin, Andrey
Publicado: (2018)

A reinforcement-learning approach to efficient communication
por: Kågebäck, Mikael, et al.
Publicado: (2020)

A Mapless Local Path Planning Approach Using Deep Reinforcement Learning Framework
por: Yin, Yan, et al.
Publicado: (2023)

Causal Impact of Type 2 Diabetes Mellitus on Cerebral Small Vessel Disease: A Mendelian Randomization Analysis
por: Liu, Junfeng, et al.
Publicado: (2018)

Causal discovery and inference: concepts and recent methodological advances
por: Spirtes, Peter, et al.
Publicado: (2016)

Review of Causal Discovery Methods Based on Graphical Models
por: Glymour, Clark, et al.
Publicado: (2019)

An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
por: Zenil, Hector, et al.
Publicado: (2019)

Experiment Selection in Meta-Analytic Piecemeal Causal Discovery
por: MATIASZ, NICHOLAS J., et al.
Publicado: (2021)

Nitric Oxide Mediates Inflammation in Type II Diabetes Mellitus through the PPARγ/eNOS Signaling Pathway
por: Guo, Hua, et al.
Publicado: (2020)

The effect of selective serotonin re-uptake inhibitors on risk of type II diabetes mellitus and acute pancreatitis: a meta-analysis
por: Yao, Shun, et al.
Publicado: (2018)

Multi-agent machine learning: a reinforcement approach
por: Schwartz, H M, et al.
Publicado: (2014)

A reinforcement learning approach to airfoil shape optimization
por: Dussauge, Thomas P., et al.
Publicado: (2023)

Prevalence of Gastroesophageal Reflux Disease in Type II Diabetes Mellitus
por: Sun, Huihui, et al.
Publicado: (2014)

Cannot write session to /tmp/vufind_sessions/sess_bd65ttthcmsltu6unf6s5indau