Machine learning techniques for the diagnosis of Alzheimer's disease: A review

M Tanveer, B Richhariya, RU Khan… - ACM Transactions on …, 2020 - dl.acm.org
Alzheimer's disease is an incurable neurodegenerative disease primarily affecting the
elderly population. Efficient automated techniques are needed for early diagnosis of …

Knowledge discovery in medicine: Current issue and future trend

N Esfandiari, MR Babavalian, AME Moghadam… - Expert Systems with …, 2014 - Elsevier
Data mining is a powerful method to extract knowledge from data. Raw data faces various
challenges that make traditional method improper for knowledge extraction. Data mining is …

Predictive markers for AD in a multi-modality framework: an analysis of MCI progression in the ADNI population

C Hinrichs, V Singh, G Xu, SC Johnson… - Neuroimage, 2011 - Elsevier
Alzheimer's Disease (AD) and other neurodegenerative diseases affect over 20 million
people worldwide, and this number is projected to significantly increase in the coming …

A novel approach of CT images feature analysis and prediction to screen for corona virus disease (COVID-19)

AA Farid, GI Selim, HAA Khater - 2020 - preprints.org
The paper demonstrates the analysis of Corona Virus Disease based on a probabilistic
model. It involves a technique for classification and prediction by recognizing typical and …

Neuroimaging and machine learning for dementia diagnosis: recent advancements and future prospects

MR Ahmed, Y Zhang, Z Feng, B Lo… - IEEE reviews in …, 2018 - ieeexplore.ieee.org
Dementia, a chronic and progressive cognitive declination of brain function caused by
disease or impairment, is becoming more prevalent due to the aging population. A major …

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey

A Alberdi, A Aztiria, A Basarab - Artificial intelligence in medicine, 2016 - Elsevier
Abstract Introduction The number of Alzheimer's Disease (AD) patients is increasing with
increased life expectancy and 115.4 million people are expected to be affected in 2050 …

Comparative analysis of various machine learning algorithms for detecting dementia

D Bansal, R Chhikara, K Khanna, P Gupta - Procedia computer science, 2018 - Elsevier
Nowadays, there has been recent interest in applying machine learning techniques to the
neurodegenerative disorders. Dementia is one such emerging global health issue and its …

NMF-SVM based CAD tool applied to functional brain images for the diagnosis of Alzheimer's disease

P Padilla, M López, JM Górriz, J Ramirez… - … on medical imaging, 2011 - ieeexplore.ieee.org
This paper presents a novel computer-aided diagnosis (CAD) technique for the early
diagnosis of the Alzheimer's disease (AD) based on nonnegative matrix factorization (NMF) …

Principal component analysis-based techniques and supervised classification schemes for the early detection of Alzheimer's disease

M López, J Ramírez, JM Górriz, I Álvarez… - Neurocomputing, 2011 - Elsevier
In Alzheimer's disease (AD) diagnosis process, functional brain image modalities such as
Single-Photon Emission Computed Tomography (SPECT) and Positron Emission …

Dental diagnosis from X-ray images: an expert system based on fuzzy computing

TM Tuan, H Fujita, N Dey, AS Ashour, VTN Ngoc… - … Signal Processing and …, 2018 - Elsevier
Background Computerized medical diagnosis systems from X-Ray images are of great
interest to physicians for accurate decision making of possible diseases and treatments …