Article
Biodiversity Conservation
Denes Schmera, Pierre Legendre, Tibor Eros, Monika Toth, Eniko K. Magyari, Bruno Baur, Janos Podani
Summary: This article discusses the methods for studying directional changes in species turnover in communities. By combining measures of community overlap and species loss/gain, a variety of turnover and nestedness concepts are defined and new measures are developed. These new measures reveal directional responses of communities to ecological gradients, uncovering an aspect of community ecology that has not been previously discovered.
ECOLOGICAL INDICATORS
(2022)
Article
Computer Science, Interdisciplinary Applications
Lukun Zheng, Yuhang Jiang
Summary: The article discusses the changes in research fields and the need to quantify the dissimilarity between scientific publications. It introduces a new measure of evolution combining 12 keyword-based temporal dissimilarities using principal component analysis. The results show the overall decreasing trend in evolution across different research fields.
Article
Geriatrics & Gerontology
Samira A. Maboudian, Ming Hsu, Zhihao Zhang
Summary: This study introduces a method for analyzing verbal fluency data using recurrence analysis and proposes a new metric, DfD, to quantify semantic fluency data. The method is applied to compare Alzheimer's disease patients and healthy controls, showing significant differences in DfD between the two groups and complementing existing metrics in diagnostic prediction. Additionally, the visualization method allows for comparison of aggregate recall data at the group level.
FRONTIERS IN AGING NEUROSCIENCE
(2022)
Article
Geriatrics & Gerontology
Xiaowei Zheng, Bozhi Wang, Hao Liu, Wencan Wu, Jiamin Sun, Wei Fang, Rundong Jiang, Yajie Hu, Cheng Jin, Xin Wei, Steve Shyh-Ching Chen
Summary: This study recommended the integration of EEG features of spectrum, complexity, and synchronization for aiding the diagnosis of AD. Three supervised machine learning classification algorithms were compared, and they achieved high accuracy in classifying AD and normal subjects based on processed EEG signal features.
FRONTIERS IN AGING NEUROSCIENCE
(2023)
Article
Clinical Neurology
Hang Yu, Manli Wang, Qiu Yang, Xiaojiao Xu, Rong Zhang, Xi Chen, Weidong Le
Summary: We propose that there may be alterations in the cerebellar electrophysiology and sleep-wake cycles at the early stage of Alzheimer's disease (AD), before the appearance of amyloid-beta neuropathological hallmarks. The characteristics of cerebellar electrophysiology could potentially serve as a biomarker for the prepathological detection of AD. Sleep disturbances are common in preclinical AD patients, and the structure and function of the cerebellum may be altered early on in the disease, suggesting its possible involvement in the progression of AD.
ALZHEIMERS & DEMENTIA
(2022)
Article
Computer Science, Artificial Intelligence
Cigdem Guluzar Altintop, Fatma Latifoglu, Aynur Karayol Akin, Adnan Bayram, Murat Ciftci
Summary: In this study, a nonlinear analysis of EEG signals was performed to classify comatose patients with different GCSs. Nonlinear features were successfully extracted from EEG signals evoked by tactile and auditory stimuli, and achieved a high accuracy in classifying different levels of consciousness.
INTERNATIONAL JOURNAL OF NEURAL SYSTEMS
(2022)
Article
Biotechnology & Applied Microbiology
Qingqing Li, Xiao Wang, Zhao Hua Wang, Zhenzong Lin, Jieyi Yang, Jichun Chen, Rui Wang, Wenfeng Ye, Ya Li, Yingying Wu, Aiguo Xuan
Summary: BCG immunization in a mouse model for Alzheimer's disease significantly increased dendritic complexity, as indicated by an increase in the number of dendritic intersections and branch points, as well as an increase in the fractal dimension of hippocampal CA1 neurons.
HUMAN VACCINES & IMMUNOTHERAPEUTICS
(2022)
Article
Mathematical & Computational Biology
Julian Fuhrer, Kyrre Glette, Anais Llorens, Tor Endestad, Anne-Kristin Solbakk, Alejandro Omar Blenkmann
Summary: Information theory is a valuable tool for understanding how the brain processes information. It can analyze complex data sets and infer underlying brain mechanisms. Information-theoretical metrics have been helpful for analyzing neurophysiological recordings.
FRONTIERS IN NEUROINFORMATICS
(2023)
Review
Engineering, Multidisciplinary
Aslan Modir, Sina Shamekhi, Peyvand Ghaderyan
Summary: Alzheimer's disease is a common neurodegenerative disorder for which no known cure exists. However, preventive drug trials and therapeutic control have been developed. The development of clinical algorithms for early detection or biomarker identification has received much attention. Electroencephalogram (EEG) signal as a noninvasive and cost-effective clinical tool has potential for automatic AD detection, but there are challenges in generalizability due to recording protocols and individual differences in EEG data.
Article
Neurosciences
Taegyun Jeong, Ukeob Park, Seung Wan Kang
Summary: This study introduces a novel QEEG feature image that integrates spatial and spectral information into a single image, improving the training of deep learning algorithms with EEG data. The classification accuracy for Alzheimer's disease dementia and non-Alzheimer's disease dementia data reached 97.4%.
FRONTIERS IN NEUROSCIENCE
(2022)
Editorial Material
Neurosciences
Cheng Cheng, Cui Yang, Congcong Jia, Qingshan Wang
Summary: This article discusses the role of the cerebellum in Alzheimer's disease, focusing on changes in cerebellar electrophysiology, sleep-wake cycles, and neuropathology in a mouse model. It offers a fresh perspective on the study of cerebellar involvement in the disease.
JOURNAL OF ALZHEIMERS DISEASE
(2023)
Article
Clinical Neurology
Jeremy A. Elman, Jacob W. Vogel, Diana I. Bocancea, Rik Ossenkoppele, Anna C. van Loenhoud, Xin M. Tu, William S. Kremen
Summary: Cognitive reserve and resilience are terms used to explain interindividual variability in maintaining cognitive health in response to adverse factors. The residual method, which regresses cognition on an adverse factor and uses the residual as a measure of resilience, may complicate interpretation and be statistically inappropriate in certain circumstances. caution is advised in using and interpreting the residual-based method of cognitive resilience, with recommendations to use statistical moderation methods to quantify resilience.
ALZHEIMERS RESEARCH & THERAPY
(2022)
Review
Neurosciences
Mingrui Liu, Baohu Liu, Zelin Ye, Dongyu Wu
Summary: This study used a bibliometric approach to analyze the application of electroencephalogram (EEG) in mild cognitive impairment (MCI) from 2005 to 2022. The research emphasis has shifted from examining local brain lesions with EEG to neural network mechanisms. The use of big data and intelligent analysis methods in EEG research is becoming more important, and linking MCI to other neurological disorders and evaluating new targets for diagnosis and treatment has become a new research trend.
FRONTIERS IN NEUROSCIENCE
(2023)
Article
Clinical Neurology
Tim S. Ellison, Stefano F. Cappa, Dawne Garrett, Jean Georges, Takeshi Iwatsubo, Joel H. Kramer, Maryna Lehmann, Constantine Lyketsos, Andrea B. Maier, Jennifer Merrilees, John C. Morris, Sharon L. Naismith, Flavio Nobili, Marco Pahor, Dimity Pond, Louise Robinson, Pinar Soysal, Mathieu Vandenbulcke, Christopher J. Weber, Pieter Jelle Visser, Michael Weiner, Giovanni B. Frisoni
Summary: This study aims to provide guidance on prognosis and assessment indicators for patients with Alzheimer's clinical syndrome. A consensus was reached on priority outcomes, measures, and statements across nine domains using the Delphi method and modified GRADE criteria. This work provides clues for clinicians on the domains and relevant measurement tools that may be used to follow patients with cognitive impairment. More work is needed to develop measurement tools that are more feasible in the context of clinical routine.
ALZHEIMERS & DEMENTIA
(2023)
Article
Computer Science, Artificial Intelligence
Chenghui Zhang, Xinchun Cui, Shujun Lian, Ruyi Xiao, Hong Qiao, Shancang Li, Yue Lou, Yue Feng, Liying Zhuang, Jianzong Du, Xiaoli Liu
Summary: A new intelligent detecting algorithm for the complexity of Alzheimer's disease (AD) dynamic network was proposed based on visibility graph, revealing a shift of dynamic complexity in brain regions from frontal to temporal and occipital lobes, which correlated significantly with clinical symptoms. The small-world topological properties of the dynamic complexity network also exhibited significant differences between cognitively normal (CN) individuals and AD patients.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Information Systems
Chima S. Eke, Emmanuel Jammeh, Xinzhong Li, Camille Carroll, Stephen Pearson, Emmanuel Ifeachor
Summary: The successful development of amyloid-based biomarkers and tests for Alzheimer's disease is an important milestone in AD diagnosis. However, limitations exist in providing limited information about the disease process and inability to detect individuals before significant amyloid-beta accumulation. This study aims to identify potential blood-based non-amyloid biomarkers for early AD detection, utilizing machine learning techniques to identify 5 novel panels of non-amyloid proteins that may serve as key biomarkers of early disease with high sensitivity and specificity.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2021)
Article
Neurosciences
Ali H. Al-Nuaimi, Marina Bluma, Shaymaa S. Al-Juboori, Chima S. Eke, Emmanuel Jammeh, Lingfen Sun, Emmanuel Ifeachor
Summary: This study aims to develop robust EEG biomarkers for detecting Alzheimer's disease (AD) with clinically acceptable performance. By combining multiple EEG biomarkers, a diagnostic model with high performance was created, providing effective services for AD patients.
Article
Multidisciplinary Sciences
Sokratis Kariotis, Emmanuel Jammeh, Emilia M. Swietlik, Josephine A. Pickworth, Christopher J. Rhodes, Pablo Otero, John Wharton, James Iremonger, Mark J. Dunning, Divya Pandya, Thomas S. Mascarenhas, Niamh Errington, A. A. Roger Thompson, Casey E. Romanoski, Franz Rischard, Joe G. N. Garcia, Jason X. -J. Yuan, Tae-Hwi Schwantes An, Ankit A. Desai, Gerry Coghlan, Jim Lordan, Paul A. Corris, Luke S. Howard, Robin Condliffe, David G. Kiely, Colin Church, Joanna Pepke-Zaba, Mark Toshner, Stephen Wort, Stefan Graf, Nicholas W. Morrell, Martin R. Wilkins, Allan Lawrie, Dennis Wang, Marta Bleda, Marta Bleda, Charaka Hadinnapola, Matthias Haimel, Kate Auckland, Tobias Tilly, Jennifer M. Martin, Katherine Yates, Carmen M. Treacy, Margaret Day, Alan Greenhalgh, Debbie Shipley, Andrew J. Peacock, Val Irvine, Fiona Kennedy, Shahin Moledina, Lynsay MacDonald, Eleni Tamvaki, Anabelle Barnes, Victoria Cookson, Latifa Chentouf, Souad Ali, Shokri Othman, Lavanya Ranganathan, J. Simon R. Gibbs, Rosa DaCosta, Joy Pinguel, Natalie Dormand, Alice Parker, Della Stokes, Dipa Ghedia, Yvonne Tan, Tanaka Ngcozana, Ivy Wanjiku, Gary Polwarth, Rob V. Mackenzie Ross, Jay Suntharalingam, Mark Grover, Ali Kirby, Ali Grove, Katie White, Annette Seatter, Amanda Creaser-Myers, Sara Walker, Stephen Roney, Charles A. Elliot, Athanasios Charalampopoulos, Ian Sabroe, Abdul Hameed, Iain Armstrong, Neil Hamilton, Alex M. K. Rothman, Andrew J. Swift, James M. Wild, Florent Soubrier, Melanie Eyries, Marc Humbert, David Montani, Barbara Girerd, Laura Scelsi, Stefano Ghio, Henning Gall, Ardi Ghofrani, Harm J. Bogaard, Anton Vonk Noordegraaf, Arjan C. Houweling, Anna Huis in't Veld, Gwen Schotte
Summary: IPAH is a rare and fatal disease with heterogeneous treatment response. Unsupervised machine learning identified 3 subgroups with unique features and prognosis, improving risk stratification and providing new insights into the pathogenesis of IPAH.
NATURE COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Alcardo Alex Barakabitze, Nabajeet Barman, Arslan Ahmad, Saman Zadtootaghaj, Lingfen Sun, Maria G. Martini, Luigi Atzori
IEEE COMMUNICATIONS SURVEYS AND TUTORIALS
(2020)
Article
Computer Science, Information Systems
Opeoluwa Ore Akinsanya, Maria Papadaki, Lingfen Sun
INFORMATION AND COMPUTER SECURITY
(2020)
Article
Computer Science, Information Systems
Nabajeet Barman, Emmanuel Jammer, Seyed Ali Ghorashi, Maria G. Martini
Proceedings Paper
Biophysics
Ali H. Al-nuaimi, Emmanuel Jammeh, Lingfen Sun, Emmanuel Ifeachor
2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC)
(2017)
Proceedings Paper
Computer Science, Artificial Intelligence
Amulya Karaadi, Lingfen Sun, Is-Haka Mkwawa
2017 IEEE INTERNATIONAL CONFERENCE ON INTERNET OF THINGS (ITHINGS) AND IEEE GREEN COMPUTING AND COMMUNICATIONS (GREENCOM) AND IEEE CYBER, PHYSICAL AND SOCIAL COMPUTING (CPSCOM) AND IEEE SMART DATA (SMARTDATA)
(2017)
Proceedings Paper
Computer Science, Software Engineering
Shenghong Hu, Lingfen Sun, Chunxia Xiao, Chao Gui
2017 IEEE INTERNATIONAL CONFERENCE ON MULTIMEDIA AND EXPO (ICME)
(2017)