Beyond Statistics: A New Combinatorial Approach to Identifying Biomarker Panels for the Early Detection and Diagnosis of Alzheimer's Disease

2014 ◽  
Vol 39 (1) ◽  
pp. 211-217 ◽  
Author(s):  
Elizabeth A. Milward ◽  
Pablo Moscato ◽  
Carlos Riveros ◽  
Daniel M. Johnstone
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Combinatorial Approach ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

scholarly journals Mobilizing Collective Action for Public Health Approaches to Dementia Education

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 2-3
Author(s):  
Jennifer Severance ◽  
Susanna Luk-Jones ◽  
Griffin Melissa ◽  
Glenda Redeemer
Keyword(s):  
Public Health ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Collective Action ◽  
Public Health Department ◽  
Brain Health ◽  
Education Programs ◽  
Detection And Diagnosis ◽  
Early Detection And Diagnosis

Abstract Addressing increasing rates of Alzheimer’s disease and related dementias (ADRD) requires public health approaches including prevention, early detection and diagnosis, and outreach to low-income and minority communities facing higher risk and adverse health and economic outcomes. Communities are seeking ways to enhance cross-sector collaboration and overcome underdeveloped relationships and fragmentation that are barriers to effective public health responses. In this exploratory study, we evaluated outcomes of a community-wide effort to mobilize systems-level changes, build public awareness, and increase access to early detection services. A community-based organization, public health department, and academic institution in North Texas partnered to expand ADRD education programs and outreach for underserved communities. Nineteen community health workers were trained to provide brain health and ADRD education programs and refer to financial, legal, and social resources. Through collective action, 371 participants attended 26 education sessions delivered in English and Spanish. Forty-five percent of participants identified as non-white and 61% reported low educational attainment. Participants (n=314) completed post-surveys. As a result of training, 89% of trainees could recognize common warning signs of Alzheimer’s disease, 86% understood the importance of early detection and diagnosis, and 96% knew activities promoting cognitive health. Findings revealed strategies to increase collective action such as sharing data, establishing referral methods, and adopting dementia-friendly and age-friendly frameworks. Results show that collective action has the potential to build a community’s capacity for targeted ADRD education and improve access to early detection and brain health education for at-risk populations.

Detection of Leukemia Using Image Processing

2018 ◽  
Vol 8 (4) ◽  
pp. 61
Author(s):  
A. Sivasangari ◽  
G. Sasikumar
Keyword(s):  
Image Processing ◽  
Statistical Analysis ◽  
Early Detection ◽  
Visual Inspection ◽  
Causes Of Death ◽  
Cure Rate ◽  
Blood Disorders ◽  
Detection And Diagnosis ◽  
The Moment ◽  
Early Detection And Diagnosis

Leukemia   disease   is one   of    the   leading   causes   of death   among   human. Its  cure  rate and  prognosis   depends   mainly   on  the  early  detection   and  diagnosis  of   the  disease. At  the  moment, identification  of  blood  disorders  is  through   visual  inspection  of  microscopic  images  by  examining  changes  like  texture, geometry, colour  and   statistical  analysis  of  images . This  project  aims  to  preliminary  of  developing  a  detection  of  leukemia  types  using   microscopic  blood  sample using MATLAB. Images  are  used  as  they  are  cheap  and  do  not  expensive  for testing  and  lab  equipment.

Development and Evaluation of a Tactile Cognitive Function Test Device for Alzheimer’s Disease Early Detection

2015 ◽  
Vol 3 (2) ◽  
pp. 58-65 ◽  
Author(s):  
Jiajia Yang ◽  
Mohd Usairy Syafiq ◽  
Yinghua Yu ◽  
Satoshi Takahashi ◽  
Zhenxin Zhang ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Function ◽  
Early Detection ◽  
Test Device ◽  
Function Test ◽  
Cognitive Function Test

scholarly journals Early Detection of Alzheimer’s Disease Using Polar Harmonic Transforms and Optimized Wavelet Neural Network

2021 ◽  
Vol 11 (4) ◽  
pp. 1574
Author(s):  
Shabana Urooj ◽  
Satya P. Singh ◽  
Areej Malibari ◽  
Fadwa Alrowais ◽  
Shaeen Kalathil
Keyword(s):  
Neural Network ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Differential Evolution ◽  
Early Stage ◽  
Selection Process ◽  
Parameter Tuning ◽  
Wavelet Neural Network ◽  
Tuning Parameter

Effective and accurate diagnosis of Alzheimer’s disease (AD), as well as early-stage detection, has gained more and more attention in recent years. For AD classification, we propose a new hybrid method for early detection of Alzheimer’s disease (AD) using Polar Harmonic Transforms (PHT) and Self-adaptive Differential Evolution Wavelet Neural Network (SaDE-WNN). The orthogonal moments are used for feature extraction from the grey matter tissues of structural Magnetic Resonance Imaging (MRI) data. Irrelevant features are removed by the feature selection process through evaluating the in-class and among-class variance. In recent years, WNNs have gained attention in classification tasks; however, they suffer from the problem of initial parameter tuning, parameter setting. We proposed a WNN with the self-adaptation technique for controlling the Differential Evolution (DE) parameters, i.e., the mutation scale factor (F) and the cross-over rate (CR). Experimental results on the Alzheimer’s disease Neuroimaging Initiative (ADNI) database indicate that the proposed method yields the best overall classification results between AD and mild cognitive impairment (MCI) (93.7% accuracy, 86.0% sensitivity, 98.0% specificity, and 0.97 area under the curve (AUC)), MCI and healthy control (HC) (92.9% accuracy, 95.2% sensitivity, 88.9% specificity, and 0.98 AUC), and AD and HC (94.4% accuracy, 88.7% sensitivity, 98.9% specificity and 0.99 AUC).

Extracellular vesicles as an emerging tool for the early detection of Alzheimer’s disease

2019 ◽  
Vol 184 ◽  
pp. 111175 ◽  
Author(s):  
Tao-Ran Li ◽  
Xiao-Ni Wang ◽  
Can Sheng ◽  
Yu-Xia Li ◽  
Frederic Zhen-Tao Li ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Early Detection ◽  
Extracellular Vesicles
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