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Purpose: This study investigates whether a machine-learning-based system can predict the rate of cognitive decline in mildly cognitively impaired patients by processing only the clinical and imaging data collected at the initial visit.…

Quantitative Methods · Quantitative Biology 2020-10-07 Sema Candemir , Xuan V. Nguyen , Luciano M. Prevedello , Matthew T. Bigelow , Richard D. White , Barbaros S. Erdal

Brain-related diseases are more sensitive than other diseases due to several factors, including the complexity of surgical procedures, high costs, and other challenges. Alzheimer's disease is a common brain disorder that causes memory loss…

Image and Video Processing · Electrical Eng. & Systems 2024-03-11 Maleka Khatun , Md Manowarul Islam , Habibur Rahman Rifat , Md. Shamim Bin Shahid , Md. Alamin Talukder , Md Ashraf Uddin

The increasing access to brain signal data using electroencephalography creates new opportunities to study electrophysiological brain activity and perform ambulatory diagnoses of neuronal diseases. This work proposes a pairwise distance…

Machine Learning · Computer Science 2019-09-09 David Calhas , Enrique Romero , Rui Henriques

Patients with semantic dementia (SD) present with remarkably consistent atrophy of neurons in the anterior temporal lobe and behavioural impairments, such as graded loss of category knowledge. While relearning of lost knowledge has been…

Machine Learning · Computer Science 2025-03-06 Devon Jarvis , Verena Klar , Richard Klein , Benjamin Rosman , Andrew Saxe

Measuring transient functional connectivity is an important challenge in Electroencephalogram (EEG) research. Here, the rich potential for insightful, discriminative information of brain activity offered by high temporal resolution is…

Neurons and Cognition · Quantitative Biology 2025-02-11 Om Roy , Yashar Moshfeghi , Agustin Ibanez , Francisco Lopera , Mario A Parra , Keith M Smith

Human mentality develops with age and is altered in psychiatric disorders, though their underlying mechanism is unknown. In this study, we analyzed nanometer-scale three-dimensional structures of brain tissues of the anterior cingulate…

Multiple Sclerosis (MS) is a chronic disease developed in human brain and spinal cord, which can cause permanent damage or deterioration of the nerves. The severity of MS disease is monitored by the Expanded Disability Status Scale (EDSS),…

Machine Learning · Computer Science 2023-04-11 Kai Zhang , John A. Lincoln , Xiaoqian Jiang , Elmer V. Bernstam , Shayan Shams

Human memory -- the learning of new information involves changes at the synaptic level between neurons dedicated for storage of in-formation. Generally, memory is classified as Long-Term Memory and Short-Term Memory. The various types of…

Neurons and Cognition · Quantitative Biology 2019-05-07 Qazi Emad-Ul-Haq , Muhammad Hussain , Hatim Aboalsamh , Saeed Bamatraf , Aamir Saeed Malik , Hafeez Ullah Amin

Subjective cognitive decline (SCD) is a preclinical stage of Alzheimer's disease (AD) which occurs even before mild cognitive impairment (MCI). Progressive SCD will convert to MCI with the potential of further evolving to AD. Therefore,…

Computer Vision and Pattern Recognition · Computer Science 2023-02-17 Hao Guan , Ling Yue , Pew-Thian Yap , Shifu Xiao , Andrea Bozoki , Mingxia Liu

First-episode schizophrenia (FES) results in abnormality of brain connectivity at different levels. Despite some successful findings on functional and structural connectivity of FES, relatively few studies have been focused on morphological…

Neurons and Cognition · Quantitative Biology 2022-12-27 Mowen Yin , Weikai Huang , Zhichao Liang , Quanying Liu , Xiaoying Tang

Recently, there has been a growing interest in monitoring brain activity for individual recognition system. So far these works are mainly focussing on single channel data or fragment data collected by some advanced brain monitoring…

Computer Vision and Pattern Recognition · Computer Science 2018-01-18 Lei Chu , Robert Qiu , Haichun Liu , Zenan Ling , Tianhong Zhang , Jijun Wang

Functional magnetic resonance imaging (fMRI) is a neuroimaging technique that records neural activations in the brain by capturing the blood oxygen level in different regions based on the task performed by a subject. Given fMRI data, the…

Computer Vision and Pattern Recognition · Computer Science 2021-09-21 Ashish Jaiswal , Ashwin Ramesh Babu , Mohammad Zaki Zadeh , Fillia Makedon , Glenn Wylie

Both functional and structural magnetic resonance imaging (fMRI and sMRI) are widely used for the diagnosis of mental disorder. However, combining complementary information from these two modalities is challenging due to their…

Image and Video Processing · Electrical Eng. & Systems 2024-04-02 Ziyu Zhou , Anton Orlichenko , Gang Qu , Zening Fu , Vince D Calhoun , Zhengming Ding , Yu-Ping Wang

Coherence is a widely used measure to assess linear relationships between time series. However, it fails to capture nonlinear dependencies. To overcome this limitation, this paper introduces the notion of residual spectral density as a…

Statistics Theory · Mathematics 2024-05-21 Yuichi Goto , Xuze Zhang , Benjamin Kedem , Shuo Chen

Structural magnetic resonance imaging (MRI) can be used to detect lesions in the brains of multiple sclerosis (MS) patients. The formation of these lesions is a complex process involving inflammation, tissue damage, and tissue repair, all…

Clinical practice in psychiatry is burdened with the increased demand for healthcare services and the scarce resources available. New paradigms of health data powered with machine learning techniques could open the possibility to improve…

Artificial Intelligence · Computer Science 2023-06-08 Juan Sebastian Canas , Francisco Gomez , Omar Costilla-Reyes

Alzheimer's Disease is a progressive neurological disorder that is one of the most common forms of dementia. It leads to a decline in memory, reasoning ability, and behavior, especially in older people. The cause of Alzheimer's Disease is…

Machine Learning · Computer Science 2025-04-03 Jing Wang , Jun-En Ding , Feng Liu , Elisa Kallioniemi , Shuqiang Wang , Wen-Xiang Tsai , Albert C. Yang

We exploit altered patterns in brain functional connectivity as features for automatic discriminative analysis of neuropsychiatric patients. Deep learning methods have been introduced to functional network classification only very recently…

Machine Learning · Computer Science 2020-04-27 Chun-Ren Phang , Chee-Ming Ting , Fuad Noman , Hernando Ombao

Dynamical brain state transitions are critical for flexible working memory but the network mechanisms are incompletely understood. Here, we show that working memory entails brainwide switching between activity states. The stability of…

Schizophrenia (SZ) is a severe brain disorder marked by diverse cognitive impairments, abnormalities in brain structure, function, and genetic factors. Its complex symptoms and overlap with other psychiatric conditions challenge traditional…

Computer Vision and Pattern Recognition · Computer Science 2024-07-30 Nagur Shareef Shaik , Teja Krishna Cherukuri , Vince D. Calhoun , Dong Hye Ye
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