Abstract
In this study, we aimed to classify MR images for recognizing Alzheimer Disease (AD) in a group of patients who were recently diagnosed by clinical history and neuropsychiatric exams by using non-biased machine-learning techniques. T1 weighted MRI scans of 31 patients with probable AD and 31 age- and gender-matched cognitively normal elderly were analyzed with voxel-based morphometry and classified by support vector machine (SVM), a machine learning technique. SVM could differentiate patients from controls with accuracy of 74 % (sensitivity: 70 % and specificity: 77 %) when the whole brain was included the analyses. The classification accuracy was increased to 79 % (sensitivity: 65 % and specificity: 93 %) when the analyses restricted to hippocampus. Our results showed that SVM is a promising tool for diagnosis of AD, but needed to be improved.
Keywords: Alzheimer’s disease, classification, diagnoses, support vector machines, hippocampus, magnetic resonance imaging, hippocampus, cardiovascular disease.
Current Alzheimer Research
Title:Computer based Classification of MR Scans in First Time Applicant Alzheimer Patients
Volume: 9 Issue: 7
Author(s): Fatma Polat, Selcuk Orhan Demirel, Omer Kitis, Fatma Simsek, Damla Isman Haznedaroglu, Kerry Coburn, Emre Kumral and Ali Saffet Gonul
Affiliation:
Keywords: Alzheimer’s disease, classification, diagnoses, support vector machines, hippocampus, magnetic resonance imaging, hippocampus, cardiovascular disease.
Abstract: In this study, we aimed to classify MR images for recognizing Alzheimer Disease (AD) in a group of patients who were recently diagnosed by clinical history and neuropsychiatric exams by using non-biased machine-learning techniques. T1 weighted MRI scans of 31 patients with probable AD and 31 age- and gender-matched cognitively normal elderly were analyzed with voxel-based morphometry and classified by support vector machine (SVM), a machine learning technique. SVM could differentiate patients from controls with accuracy of 74 % (sensitivity: 70 % and specificity: 77 %) when the whole brain was included the analyses. The classification accuracy was increased to 79 % (sensitivity: 65 % and specificity: 93 %) when the analyses restricted to hippocampus. Our results showed that SVM is a promising tool for diagnosis of AD, but needed to be improved.
Export Options
About this article
Cite this article as:
Polat Fatma, Orhan Demirel Selcuk, Kitis Omer, Simsek Fatma, Isman Haznedaroglu Damla, Coburn Kerry, Kumral Emre and Saffet Gonul Ali, Computer based Classification of MR Scans in First Time Applicant Alzheimer Patients, Current Alzheimer Research 2012; 9 (7) . https://dx.doi.org/10.2174/156720512802455359
DOI https://dx.doi.org/10.2174/156720512802455359 |
Print ISSN 1567-2050 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5828 |
Call for Papers in Thematic Issues
New Advances in the Prevention, Diagnosis, Treatment, and Rehabilitation of Alzheimer's Disease
Aims and Scope: Introduction: Alzheimer's disease (AD) poses a significant global health challenge, with an increasing prevalence that demands concerted efforts to advance our understanding and strategies for prevention, diagnosis, treatment, and rehabilitation. This thematic issue aims to bring together cutting-edge research and innovative approaches from multidisciplinary perspectives to address ...read more
Current updates on the Role of Neuroinflammation in Neurodegenerative Disorders
Neuroinflammation is an invariable hallmark of chronic and acute neurodegenerative disorders and has long been considered a potential drug target for Alzheimer?s disease (AD) and dementia. Significant evidence of inflammatory processes as a feature of AD is provided by the presence of inflammatory markers in plasma, CSF and postmortem brain ...read more
Deep Learning for Advancing Alzheimer's Disease Research
Alzheimer's disease (AD) poses a significant global health challenge, with an increasing number of individuals affected yearly. Deep learning, a subfield of artificial intelligence, has shown immense potential in various domains, including healthcare. This thematic issue of Current Alzheimer Research explores the application of deep learning techniques in advancing our ...read more
Diagnostic and therapeutic biomarkers of dementia
Dementia affects 18 million people worldwide. Dementia is a syndrome of symptoms caused by brain disease, usually chronic or progressive, clinically characterized by multiple impairments of higher cortical functions such as memory, thinking, orientation, and learning. In addition, in the course of dementia, cognitive deficits are observed, which often hinder ...read more
- Author Guidelines
- Graphical Abstracts
- Fabricating and Stating False Information
- Research Misconduct
- Post Publication Discussions and Corrections
- Publishing Ethics and Rectitude
- Increase Visibility of Your Article
- Archiving Policies
- Peer Review Workflow
- Order Your Article Before Print
- Promote Your Article
- Manuscript Transfer Facility
- Editorial Policies
- Allegations from Whistleblowers
- Announcements
Related Articles
-
Maternal Vitamin D Status and Development of Asthma and Allergy in Early Childhood
Mini-Reviews in Medicinal Chemistry The Development of Preventives and Therapeutics for Alzheimers Disease that Inhibit the Formation of β-Amyloid Fibrils (fAβ), as Well as Destabilize Preformed fAβ
Current Pharmaceutical Design Interleukin-18, From Neuroinflammation to Alzheimers Disease
Current Pharmaceutical Design Preface
Current Genomics Phosphodiesterase Inhibitors for Cognitive Enhancement
Current Pharmaceutical Design Gender Differences in Pharmacokinetics and Side Effects of Second Generation Antipsychotic Drugs
Current Neuropharmacology Longevity Pathways: HSF1 and FoxO Pathways, a New Therapeutic Target to Prevent Age-Related Diseases
Current Aging Science Multicenter Randomized Controlled Trial for the Treatment of Ulcerative Colitis with a Leukocytapheresis Column
Current Pharmaceutical Design Visualising Neuroinflammation in Post-Stroke Patients: A Comparative PET Study with the TSPO Molecular Imaging Biomarkers [<sup>11</sup>C]PK11195 and [<sup>11</sup>C]vinpocetine
Current Radiopharmaceuticals A Multicentre Italian Validation Study in Aging Adults with Down Syndrome and Other Forms of Intellectual Disabilities: Dementia Screening Questionnaire for Individuals with Intellectual Disabilities
Current Alzheimer Research Insulin Resistance in Alzheimer Disease: p53 and MicroRNAs as Important Players
Current Topics in Medicinal Chemistry Establishing Genomic/Transcriptomic Links Between Alzheimer’s Disease and Type 2 Diabetes Mellitus by Meta-Analysis Approach
CNS & Neurological Disorders - Drug Targets Diagnosis and Management of Endocrine Hypertension in Children and Adolescents
Current Pharmaceutical Design Diabetes Mellitus to Neurodegenerative Disorders: Is Oxidative Stress Fueling the Flame?
CNS & Neurological Disorders - Drug Targets Treatment Approaches in Elderly Patients with Head and Neck Cancer
Anti-Cancer Agents in Medicinal Chemistry Cognitive Dysfunction in Depression – Pathophysiology and Novel Targets
CNS & Neurological Disorders - Drug Targets Novel Indole-Isoxazole Hybrids: Synthesis and In Vitro Anti-Cholinesterase Activity
Letters in Drug Design & Discovery Kinetic Study on the Effects of Extremely Low Frequency Electromagnetic Field on Catalase, Cytochrome P450 and Inducible Nitric Oxide Synthase in Human HaCaT and THP-1 Cell Lines
CNS & Neurological Disorders - Drug Targets MRI of Central Nervous System (CNS) Vasculitis
Current Medical Imaging 5-HT1 Receptors
Current Drug Targets - CNS & Neurological Disorders