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على هادي حسين - Ali Al-nuaimi
PhD - lecturer
College of Education for Pure Sciences (Ibn Al-Haitham) , Deparment of Computer Science
[email protected]
Summary

Dr Ali Al-Nuaimi was awarded a Ph.D. in bioinformatics from the University of Plymouth, Plymouth, U.K., the M.Sc. degree in digital signal processing from University of Baghdad, Baghdad, Iraq, and the B.Sc. degree in computer science. Currently, he is a lecturer at the University of Baghdad. He has published premium research papers in the areas of biomedical signal processing and machine learning, including book chapters. He has published extensively, presented at international conferences, and a reviewer for many journals and conferences.

Qualifications

PhD Computer Science, MSc Computer Science, BSc Computer Science

Research Interests

Machine Learning / Deep Learning, Bioinformatics, Biomedical Signal Processing, EEG Biomarkers, and EG Analysis

Academic Area

Bioinformatics, Data Analysis

Teaching

Machine Learning, Deep Learning, Image Processing, and Signal Processing

Publication Date
Mon Jan 01 2018
Journal Name
Complexity
Complexity Measures for Quantifying Changes in Electroencephalogram in Alzheimer’s Disease

Alzheimer’s disease (AD) is a progressive disorder that affects cognitive brain functions and starts many years before its clinical manifestations. A biomarker that provides a quantitative measure of changes in the brain due to AD in the early stages would be useful for early diagnosis of AD, but this would involve dealing with large numbers of people because up to 50% of dementia sufferers do not receive formal diagnosis. Thus, there is a need for accurate, low-cost, and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, electroencephalogram (EEG) based biomarkers can play a vital role in early diagnosis of AD as they can fulfill these needs. This is a cross-sectional study that aims to demon

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Publication Date
Sat Jul 31 2021
Journal Name
Brain Sciences
Robust EEG Based Biomarkers to Detect Alzheimer’s Disease

Biomarkers to detect Alzheimer’s disease (AD) would enable patients to gain access to appropriate services and may facilitate the development of new therapies. Given the large numbers of people affected by AD, there is a need for a low-cost, easy to use method to detect AD patients. Potentially, the electroencephalogram (EEG) can play a valuable role in this, but at present no single EEG biomarker is robust enough for use in practice. This study aims to provide a methodological framework for the development of robust EEG biomarkers to detect AD with a clinically acceptable performance by exploiting the combined strengths of key biomarkers. A large number of existing and novel EEG biomarkers associated with slowing of EEG, reductio

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Publication Date
Wed Mar 23 2011
Journal Name
Ibn Al- Haitham J. For Pure & Appl. Sci.
Image Compression Using Proposed Enhanced Run Length Encoding Algorithm

In this paper, we will present proposed enhance process of image compression by using RLE algorithm. This proposed yield to decrease the size of compressing image, but the original method used primarily for compressing a binary images [1].Which will yield increasing the size of an original image mostly when used for color images. The test of an enhanced algorithm is performed on sample consists of ten BMP 24-bit true color images, building an application by using visual basic 6.0 to show the size after and before compression process and computing the compression ratio for RLE and for the enhanced RLE algorithm.

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Publication Date
Mon Aug 01 2016
Journal Name
2016 38th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Changes in the EEG amplitude as a biomarker for early detection of Alzheimer's disease

The rapid increase in the number of older people with Alzheimer's disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage in the brain due to AD leads to changes in the information processing activity of the brain and the EEG which ca

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Publication Date
Wed Jun 24 2020
Journal Name
Neuroimaging - Neurobiology, Multimodal And Network Applications
Electroencephalogram Based Biomarkers for Detection of Alzheimer’s Disease

Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n

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Publication Date
Tue Jul 11 2017
Journal Name
The 39th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc'17)
Higuchi fractal dimension of the electroencephalogram as a biomarker for early detection of Alzheimer's disease

It is widely accepted that early diagnosis of Alzheimer's disease (AD) makes it possible for patients to gain access to appropriate health care services and would facilitate the development of new therapies. AD starts many years before its clinical manifestations and a biomarker that provides a measure of changes in the brain in this period would be useful for early diagnosis of AD. Given the rapid increase in the number of older people suffering from AD, there is a need for an accurate, low-cost and easy to use biomarkers that could be used to detect AD in its early stages. Potentially, the electroencephalogram (EEG) can play a vital role in this but at present, no reliable EEG biomarker exists for early diagnosis of AD. The gradual s

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Publication Date
Mon Jun 14 2021
Journal Name
Biosense Dementia 2017 - International Workshop On Biosensors For Dementia From 13 – 14 June 2017 – Plymouth University, Plymouth, Uk
Changes in the Electroencephalogram as a Biomarker of Alzheimer’s Disease

The rapid increase in the number of older people with Alzheimer’s disease (AD) and other forms of dementia represents one of the major challenges to the health and social care systems because of a large number of people affected. Early detection of AD makes it possible for patients to access appropriate services and to benefit from new treatments and therapies, as and when they become available, and to plan for the future. The onset of AD starts many years before the clinical symptoms become clear. A biomarker that can measure the brain changes in this period would be useful for early diagnosis of AD. Potentially, the electroencephalogram (EEG) can play a valuable role in early detection of AD. Damage caused to the brain due to AD leads t

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Publication Date
Sat Aug 01 2015
Journal Name
2015 37th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Tsallis entropy as a biomarker for detection of Alzheimer's disease

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