Cargando…

XGBoost-SHAP-based interpretable diagnostic framework for alzheimer’s disease

BACKGROUND: Due to the class imbalance issue faced when Alzheimer’s disease (AD) develops from normal cognition (NC) to mild cognitive impairment (MCI), present clinical practice is met with challenges regarding the auxiliary diagnosis of AD using machine learning (ML). This leads to low diagnosis p...

Descripción completa

Detalles Bibliográficos
Autores principales:	Yi, Fuliang, Yang, Hui, Chen, Durong, Qin, Yao, Han, Hongjuan, Cui, Jing, Bai, Wenlin, Ma, Yifei, Zhang, Rong, Yu, Hongmei
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2023
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10369804/ https://www.ncbi.nlm.nih.gov/pubmed/37491248 http://dx.doi.org/10.1186/s12911-023-02238-9

Ejemplares similares

Interpretable predictive model for shield attitude control performance based on XGboost and SHAP
por: Hu, Min, et al.
Publicado: (2022)

An Interpretable Prediction Model for Identifying N(7)-Methylguanosine Sites Based on XGBoost and SHAP
por: Bi, Yue, et al.
Publicado: (2020)

Estimating Bidirectional Transitions and Identifying Predictors of Mild Cognitive Impairment
por: Qin, Yao, et al.
Publicado: (2023)

Explainable SHAP-XGBoost models for in-hospital mortality after myocardial infarction
por: Tarabanis, Constantine, et al.
Publicado: (2023)

Potential of Coupling Metaheuristics-Optimized-XGBoost and SHAP in Revealing PAHs Environmental Fate
por: Jovanovic, Gordana, et al.
Publicado: (2023)

Factors influencing secondary school students’ reading literacy: An analysis based on XGBoost and SHAP methods
por: Liu, Hao, et al.
Publicado: (2022)

Positional SHAP (PoSHAP) for Interpretation of machine learning models trained from biological sequences
por: Dickinson, Quinn, et al.
Publicado: (2022)

Detection of the chronic kidney disease using XGBoost classifier and explaining the influence of the attributes on the model using SHAP
por: Raihan, Md. Johir, et al.
Publicado: (2023)

Factors related to steroid treatment responsiveness in thyroid eye disease patients and application of SHAP for feature analysis with XGBoost
por: Park, Jungyul, et al.
Publicado: (2023)

Modeling of energy consumption factors for an industrial cement vertical roller mill by SHAP-XGBoost: a "conscious lab" approach
por: Fatahi, Rasoul, et al.
Publicado: (2022)

m5Cpred-XS: A New Method for Predicting RNA m5C Sites Based on XGBoost and SHAP
por: Liu, Yinbo, et al.
Publicado: (2022)

Ultrasound-based radiomics XGBoost model to assess the risk of central cervical lymph node metastasis in patients with papillary thyroid carcinoma: Individual application of SHAP
por: Shi, Yan, et al.
Publicado: (2022)

PPSW–SHAP: Towards Interpretable Cell Classification Using Tree-Based SHAP Image Decomposition and Restoration for High-Throughput Bright-Field Imaging
por: Goktas, Polat, et al.
Publicado: (2023)

Hierarchical multi-class Alzheimer’s disease diagnostic framework using imaging and clinical features
por: Qin, Yao, et al.
Publicado: (2022)

GPUTreeShap: massively parallel exact calculation of SHAP scores for tree ensembles
por: Mitchell, Rory, et al.
Publicado: (2022)

Explainable AI for Retinoblastoma Diagnosis: Interpreting Deep Learning Models with LIME and SHAP
por: Aldughayfiq, Bader, et al.
Publicado: (2023)

The importance of interpreting machine learning models for blood glucose prediction in diabetes: an analysis using SHAP
por: Prendin, Francesco, et al.
Publicado: (2023)

How to understand high global food price? Using SHAP to interpret machine learning algorithm
por: Han, Xiao, et al.
Publicado: (2023)

A hybrid stacked ensemble and Kernel SHAP-based model for intelligent cardiotocography classification and interpretability
por: Feng, Junyuan, et al.
Publicado: (2023)

The complete chloroplast genome of Alhagi sparsifolia Shap. (Leguminosae)
por: Jiang, Xi, et al.
Publicado: (2021)

SHAP and LIME: An Evaluation of Discriminative Power in Credit Risk
por: Gramegna, Alex, et al.
Publicado: (2021)

XGBoost-Based Framework for Smoking-Induced Noncommunicable Disease Prediction
por: Davagdorj, Khishigsuren, et al.
Publicado: (2020)

Identifying key multi-modal predictors of incipient dementia in Parkinson’s disease: a machine learning analysis and Tree SHAP interpretation
por: McFall, G. Peggy, et al.
Publicado: (2023)

Fraud Detection in Mobile Payment Systems using an XGBoost-based Framework
por: Hajek, Petr, et al.
Publicado: (2022)

The path linking disease severity and cognitive function with quality of life in Parkinson’s disease: the mediating effect of activities of daily living and depression
por: He, Yao, et al.
Publicado: (2021)

A Novel Protein Subcellular Localization Method With CNN-XGBoost Model for Alzheimer's Disease
por: Pang, Long, et al.
Publicado: (2019)

Interpretable Predictive Modelling of Basalt Fiber Reinforced Concrete Splitting Tensile Strength Using Ensemble Machine Learning Methods and SHAP Approach
por: Cakiroglu, Celal, et al.
Publicado: (2023)

SHAPS-C: the Snaith-Hamilton pleasure scale modified for clinician administration
por: Ameli, Rezvan, et al.
Publicado: (2014)

Unboxing Industry-Standard AI Models for Male Fertility Prediction with SHAP
por: GhoshRoy, Debasmita, et al.
Publicado: (2023)

Machine learning explainability in nasopharyngeal cancer survival using LIME and SHAP
por: Alabi, Rasheed Omobolaji, et al.
Publicado: (2023)

Addressing Internet of Things security by enhanced sine cosine metaheuristics tuned hybrid machine learning model and results interpretation based on SHAP approach
por: Dobrojevic, Milos, et al.
Publicado: (2023)

Traditional Uses, Chemistry, Pharmacology, Toxicology and Quality Control of Alhagi sparsifolia Shap.: A Review
por: Wei, Feng, et al.
Publicado: (2021)

Psychometric properties the of Brazilian Portuguese version of Snaith-Hamilton Pleasure Scale (SHAPS)
por: Jesus-Nunes, Ana Paula, et al.
Publicado: (2021)

How can SHAP values help to shape metabolic stability of chemical compounds?
por: Wojtuch, Agnieszka, et al.
Publicado: (2021)

Classification and Explanation for Intrusion Detection System Based on Ensemble Trees and SHAP Method
por: Le, Thi-Thu-Huong, et al.
Publicado: (2022)

Application of SHAP values for inferring the optimal functional form of covariates in pharmacokinetic modeling
por: Janssen, Alexander, et al.
Publicado: (2022)

Gray matter volume drives the brain age gap in schizophrenia: a SHAP study
por: Ballester, Pedro L., et al.
Publicado: (2023)

Predicting response to CCRT for esophageal squamous carcinoma by a radiomics-clinical SHAP model
por: Cheng, Xu, et al.
Publicado: (2023)

Prediction Framework on Early Urine Infection in IoT–Fog Environment Using XGBoost Ensemble Model
por: Gupta, Aditya, et al.
Publicado: (2023)

A Modified Aquila-Based Optimized XGBoost Framework for Detecting Probable Seizure Status in Neonates
por: Mumenin, Khondoker Mirazul, et al.
Publicado: (2023)

Cannot write session to /tmp/vufind_sessions/sess_ot7da3r0jgdfhlot4gr48o7b5c