Deep learning for smart Healthcare—A survey on brain tumor detection from medical imaging

M Arabahmadi, R Farahbakhsh, J Rezazadeh - Sensors, 2022 - mdpi.com
Advances in technology have been able to affect all aspects of human life. For example, the
use of technology in medicine has made significant contributions to human society. In this …

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 …

Machine learning techniques for diagnosis of alzheimer disease, mild cognitive disorder, and other types of dementia

G Mirzaei, H Adeli - Biomedical Signal Processing and Control, 2022 - Elsevier
Alzheimer's disease (AD) is one of the most common form of dementia which mostly affects
elderly people. AD identification in early stages is a difficult task in medical practice and …

Automated EEG-based screening of depression using deep convolutional neural network

UR Acharya, SL Oh, Y Hagiwara, JH Tan… - Computer methods and …, 2018 - Elsevier
In recent years, advanced neurocomputing and machine learning techniques have been
used for Electroencephalogram (EEG)-based diagnosis of various neurological disorders. In …

Early diagnosis of Alzheimer's disease using machine learning: a multi-diagnostic, generalizable approach

VS Diogo, HA Ferreira, D Prata… - Alzheimer's Research & …, 2022 - Springer
Background Early and accurate diagnosis of Alzheimer's disease (AD) is essential for
disease management and therapeutic choices that can delay disease progression. Machine …

Parkinson's disease: Cause factors, measurable indicators, and early diagnosis

S Bhat, UR Acharya, Y Hagiwara, N Dadmehr… - Computers in biology …, 2018 - Elsevier
Parkinson's disease (PD) is a neurodegenerative disease of the central nervous system
caused due to the loss of dopaminergic neurons. It is classified under movement disorder as …

Automated MRI-based deep learning model for detection of Alzheimer's disease process

W Feng, NV Halm-Lutterodt, H Tang… - … Journal of Neural …, 2020 - World Scientific
In the context of neuro-pathological disorders, neuroimaging has been widely accepted as a
clinical tool for diagnosing patients with Alzheimer's disease (AD) and mild cognitive …

Artificial intelligence techniques for automated diagnosis of neurological disorders

U Raghavendra, UR Acharya, H Adeli - European neurology, 2020 - karger.com
Background: Authors have been advocating the research ideology that a computer-aided
diagnosis (CAD) system trained using lots of patient data and physiological signals and …

[HTML][HTML] Applications of artificial intelligence to aid early detection of dementia: a sco** review on current capabilities and future directions

R Li, X Wang, K Lawler, S Garg, Q Bai, J Alty - Journal of biomedical …, 2022 - Elsevier
Abstract Background & Objective With populations aging, the number of people with
dementia worldwide is expected to triple to 152 million by 2050. Seventy percent of cases …

A comprehensive survey on the detection, classification, and challenges of neurological disorders

AA Lima, MF Mridha, SC Das, MM Kabir, MR Islam… - Biology, 2022 - mdpi.com
Simple Summary This study represents a resourceful review article that can deliver
resources on neurological diseases and their implemented classification algorithms to …