Machine Learning Approaches for Predicting Progression to Alzheimer’s Disease in Patients with Mild Cognitive ImpairmentMachine Learning Approaches for Predicting Progression to Alzheimer’s Disease in Patients with Mild Cognitive ImpairmentF. Gelir et al.

被引：1

作者：

Fatih Gelir ^{[1
]}

Taymaz Akan ^{[1
]}

Sait Alp ^{[2
]}

Emrah Gecili ^{[3
]}

Md. Shenuarin Bhuiyan ^{[4
]}

Elizabeth A. Disbrow ^{[5
]}

Steven A. Conrad ^{[11
]}

John A. Vanchiere ^{[6
]}

Christopher G. Kevil ^{[7
]}

Mohammad Alfrad Nobel Bhuiyan ^{[8
]}

机构：

[1] Louisiana State University Health Sciences Center at Shreveport,Department of Medicine

[2] Trabzon University,Department of Artificial Intelligence Engineering

[3] Cincinnati Children’s Hospital Medical Center,Division of Biostatistics and Epidemiology

[4] University of Cincinnati,Department of Pediatrics

[5] Louisiana State University Health Sciences Center at Shreveport,Department of Pathology and Translational Pathobiology

[6] Louisiana State University Health Sciences Center at Shreveport,Department of Pharmacology

[7] Louisiana State University Health Sciences Center at Shreveport,Center for Brain Health

[8] Louisiana State University Health Sciences Center at Shreveport,Department of Neurology

[9] Louisiana State University Health Sciences Center at Shreveport,Department of Psychiatry

[10] Louisiana State University Health Sciences Center at Shreveport,Department of Pediatrics

[11] Louisiana State University Health Sciences Center at Shreveport,Department of Molecular and Cellular Physiology

来源：

关键词：

Alzheimer's disease; Machine learning; Shapley value explanation technique; Feature selection; Balancing;

D O I：

10.1007/s40846-024-00918-z

中图分类号：

学科分类号：

摘要：

引用

页码：63 / 83

页数：20