Cargando…

A Machine Learning Method for Identifying Critical Interactions Between Gene Pairs in Alzheimer's Disease Prediction

Background: Alzheimer's disease (AD) is the most common type of dementia. Scientists have discovered that the causes of AD may include a combination of genetic, lifestyle, and environmental factors, but the exact cause has not yet been elucidated. Effective strategies to prevent and treat AD th...

Descripción completa

Detalles Bibliográficos
Autores principales:	Chen, Hao, He, Yong, Ji, Jiadong, Shi, Yufeng
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2019
Materias:	Neurology
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6834789/ https://www.ncbi.nlm.nih.gov/pubmed/31736866 http://dx.doi.org/10.3389/fneur.2019.01162

Ejemplares similares

Machine learning approach for hemorrhagic transformation prediction: Capturing predictors' interaction
por: Elsaid, Ahmed F., et al.
Publicado: (2022)

Using machine learning to identify gene interaction networks associated with breast cancer
por: Liu, Liyuan, et al.
Publicado: (2022)

Comparison of Transfer Learning and Conventional Machine Learning Applied to Structural Brain MRI for the Early Diagnosis and Prognosis of Alzheimer's Disease
por: Nanni, Loris, et al.
Publicado: (2020)

Machine learning in the prediction of post-stroke cognitive impairment: a systematic review and meta-analysis
por: Li, XiaoSheng, et al.
Publicado: (2023)

Constructing Prediction Models for Freezing of Gait by Nomogram and Machine Learning: A Longitudinal Study
por: Xu, Kun, et al.
Publicado: (2021)

Predicting 6-Month Unfavorable Outcome of Acute Ischemic Stroke Using Machine Learning
por: Li, Xiang, et al.
Publicado: (2020)

Machine Learning-Based Framework for Differential Diagnosis Between Vascular Dementia and Alzheimer's Disease Using Structural MRI Features
por: Zheng, Yineng, et al.
Publicado: (2019)

Machine Learning in Action: Stroke Diagnosis and Outcome Prediction
por: Mainali, Shraddha, et al.
Publicado: (2021)

Editorial: Machine Learning in Neuroimaging
por: Federau, Christian, et al.
Publicado: (2021)

Editorial: Machine Learning in Action: Stroke Diagnosis and Outcome Prediction
por: Abedi, Vida, et al.
Publicado: (2022)

Interpretable Machine Learning Modeling for Ischemic Stroke Outcome Prediction
por: Jabal, Mohamed Sobhi, et al.
Publicado: (2022)

Machine learning-based prediction of symptomatic intracerebral hemorrhage after intravenous thrombolysis for stroke: a large multicenter study
por: Wen, Rui, et al.
Publicado: (2023)

Machine learning for infection risk prediction in postoperative patients with non-mechanical ventilation and intravenous neurotargeted drugs
por: Du, Yi, et al.
Publicado: (2022)

Predicting 30-Day Readmission for Stroke Using Machine Learning Algorithms: A Prospective Cohort Study
por: Chen, Yu-Ching, et al.
Publicado: (2022)

Prediction of Vestibular Dysfunction by Applying Machine Learning Algorithms to Postural Instability
por: Kamogashira, Teru, et al.
Publicado: (2020)

Predicting Vasovagal Responses: A Model-Based and Machine Learning Approach
por: Raphan, Theodore, et al.
Publicado: (2021)

Machine learning can predict mild cognitive impairment in Parkinson's disease
por: Amboni, Marianna, et al.
Publicado: (2022)

Analyzing and predicting the risk of death in stroke patients using machine learning
por: Zhu, Enzhao, et al.
Publicado: (2023)

Interpretable machine learning for prediction of clinical outcomes in acute ischemic stroke
por: Lee, Joonwon, et al.
Publicado: (2023)

Quantitative EEG parameters can improve the predictive value of the non-traumatic neurological ICU patient prognosis through the machine learning method
por: Tian, Jia, et al.
Publicado: (2022)

Identifying Morphological Patterns of Hippocampal Atrophy in Patients With Mesial Temporal Lobe Epilepsy and Alzheimer Disease
por: Duan, Yiran, et al.
Publicado: (2020)

Application of Machine Learning Techniques to Identify Data Reliability and Factors Affecting Outcome After Stroke Using Electronic Administrative Records
por: Rana, Santu, et al.
Publicado: (2021)

Integrate prediction of machine learning for single ACoA rupture risk: a multicenter retrospective analysis
por: Li, Yang, et al.
Publicado: (2023)

Automated Machine Learning Model Development for Intracranial Aneurysm Treatment Outcome Prediction: A Feasibility Study
por: Ou, Chubin, et al.
Publicado: (2021)

Application of TBSS-based machine learning models in the diagnosis of pediatric autism
por: He, Xiongpeng, et al.
Publicado: (2023)

A Novel Ensemble-Based Machine Learning Algorithm to Predict the Conversion From Mild Cognitive Impairment to Alzheimer's Disease Using Socio-Demographic Characteristics, Clinical Information, and Neuropsychological Measures
por: Grassi, Massimiliano, et al.
Publicado: (2019)

Automatic Machine-Learning-Based Outcome Prediction in Patients With Primary Intracerebral Hemorrhage
por: Wang, Hsueh-Lin, et al.
Publicado: (2019)

Predicting progression to dementia with “comprehensive visual rating scale” and machine learning algorithms
por: Park, Chaeyoon, et al.
Publicado: (2022)

Machine learning to predict in-stent stenosis after Pipeline embolization device placement
por: Wei, Dachao, et al.
Publicado: (2022)

Machine Learning in Acute Ischemic Stroke Neuroimaging
por: Kamal, Haris, et al.
Publicado: (2018)

Editorial: Machine Learning and Decision Support in Stroke
por: Liebeskind, David S., et al.
Publicado: (2020)

Editorial: Application of Machine Learning in the Diagnosis of Dementia
por: Sakatani, Kaoru, et al.
Publicado: (2022)

Objectification of intracochlear electrocochleography using machine learning
por: Schuerch, Klaus, et al.
Publicado: (2022)

Machine Learning Assisted MRI Characterization for Diagnosis of Neonatal Acute Bilirubin Encephalopathy
por: Liu, Zhou, et al.
Publicado: (2019)

Machine learning-based prediction of clinical outcomes after first-ever ischemic stroke
por: Fast, Lea, et al.
Publicado: (2023)

Radiomics and machine learning applied to STIR sequence for prediction of quantitative parameters in facioscapulohumeral disease
por: Colelli, Giulia, et al.
Publicado: (2023)

Predicting short-term outcomes in atrial-fibrillation-related stroke using machine learning
por: Jeon, Eun-Tae, et al.
Publicado: (2023)

3D genome-selected microRNAs to improve Alzheimer's disease prediction
por: Li, Keyi, et al.
Publicado: (2023)

Diagnosis of Acute Central Dizziness With Simple Clinical Information Using Machine Learning
por: Kim, Bum Joon, et al.
Publicado: (2021)

Non-Invasive Prediction of Survival Time of Midline Glioma Patients Using Machine Learning on Multiparametric MRI Radiomics Features
por: Deng, Da-Biao, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_61s116flftcmee4dfk3ihm9713