Atif Riaz

Atif Riaz
City, University of London · Department of Computer Science

Doctor of Philosophy

About

10
Publications
2,231
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248
Citations
Introduction
I am a Lecturer at the Department of Computer Science, City, University of London. My research interests are machine learning, deep learning and artificial intelligence.

Publications

Publications (10)
Article
Full-text available
Attention Deficit Hyperactivity Disorder (ADHD) is a brain disorder with characteristics such as lack of concentration, excessive fidgeting, outbursts of emotions, lack of patience, difficulty in organizing tasks, increased forgetfulness, and interrupting conversation, and it is affecting millions of people worldwide. There is, until now, not a gol...
Article
Full-text available
Autism disorder, generally known as Autism Spectrum Disorder (ASD) is a brain disorder characterized by lack of communication skills, social aloofness and repetitions in the actions in the patients, which is affecting millions of the people across the globe. Accurate identification of autistic patients is considered a challenging task in the domain...
Article
Background: Resting state fMRI has emerged as a popular neuroimaging method for automated recognition and classification of brain disorders. Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common brain disorders affecting young children, yet its underlying mechanism is not completely understood and its diagnosis is mainly depend...
Article
Resting state fMRI has emerged as a popular neuroimaging method for automated recognition and classification of different brain disorders. Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common brain disorders affecting young children, yet its underlying mechanism is not completely understood and its diagnosis is mainly dependent...
Conference Paper
Full-text available
Investigation of functional brain connectivity patterns using functional MRI has received significant interest in the neuroimaging domain. Brain functional connectivity alterations have widely been exploited for diagnosis and prediction of various brain disorders. Over the last several years, the research community has made tremendous advancements...
Article
Background and objective: The high mortality rate associated with coronary heart disease (CHD) has driven intensive research in cardiac imaging and image analysis. The advent of computed tomography angiography (CTA) has turned non-invasive diagnosis of cardiovascular anomalies into reality as calcified coronary plaques can be easily identified due...
Conference Paper
Full-text available
Attention Deficit Hyperactive Disorder (ADHD) is one of the most common disorders affecting young children, and its underlying mechanism is not completely understood. This paper proposes a phenotypic integrated machine learning framework to investigate functional connectivity alterations between ADHD and control subjects not diagnosed with ADHD, em...
Article
Full-text available
The study of functional brain connectivity alterations induced by neurological disorders and their analysis from resting state functional Magnetic Resonance Imaging (rfMRI) is generally considered to be a challenging task. The main challenge lies in determining and interpreting the large-scale connectivity of brain regions when studying neurologica...
Conference Paper
Identification of functional brain connectivity differences induced by certain neurological disorders from resting state functional MRI (rfMRI) is generally considered a difficult task. This challenging task requires the identification of discriminative neuroimaging markers. In this paper, we propose a two-stage algorithm to identify functional con...

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