Article
Clinical Neurology
Yunjun Yang, Yuelong Yang, Aizhen Pan, Zhifeng Xu, Lijuan Wang, Yuhu Zhang, Kun Nie, Biao Huang
Summary: This study investigates white matter microstructural alterations in Parkinson's disease patients with depression using the whole-brain diffusion tensor imaging (DTI) method and explores the potential of a DTI-based machine learning model in identifying depressed Parkinson's disease. The results imply that depression in Parkinson's disease is associated with changes in white matter microstructure, and the machine learning model using DTI parameters shows promise in individualized diagnosis of depressive Parkinson's disease.
FRONTIERS IN NEUROLOGY
(2022)
Article
Clinical Neurology
Ruxue Gong, Mirko Wegscheider, Christoph Muehlberg, Richard Gast, Christopher Fricke, Jost-Julian Rumpf, Vadim V. Nikulin, Thomas R. Knoesche, Joseph Classen
Summary: Abnormal phase-amplitude coupling between beta and broadband-gamma activities has been identified in recordings from patients with Parkinson's disease, particularly in specific brain regions involved in motor control. The coupling between beta and gamma signals from different components appears to have pathophysiological significance, and therapeutic approaches targeting abnormal lateral coupling between neuronal circuits may be more promising.
Article
Clinical Neurology
Ruxue Gong, Mirko Wegscheider, Christoph Muehlberg, Richard Gast, Christopher Fricke, Jost-Julian Rumpf, Vadim V. Nikulin, Thomas R. Knoesche, Joseph Classen
Summary: Abnormal phase-amplitude coupling between beta and gamma activities has been found in Parkinson's disease patients, with enhancements in specific cortical regions related to motor control. The coupling between different neural networks appears to have pathophysiological significance and may be more promising as a therapeutic target than targeting phase-amplitude coupling per se.
Article
Computer Science, Information Systems
Rui Zhang, Jian Wang, Nan Jiang, Zichen Wang
Summary: This paper proposes a quantum support vector machine based on amplitude estimation (AE-QSVM) to improve machine learning. AE-QSVM eliminates the constraint of repetitive processes and saves quantum resources. The experimental results demonstrate that classification with a 95% probability of success only uses 12 qubits.
INFORMATION SCIENCES
(2023)
Article
Geriatrics & Gerontology
Dafa Shi, Haoran Zhang, Guangsong Wang, Siyuan Wang, Xiang Yao, Yanfei Li, Qiu Guo, Shuang Zheng, Ke Ren
Summary: Parkinson's disease is a common degenerative disease with challenging diagnosis. This study successfully classified patients with Parkinson's disease and healthy controls using radiomics features and machine learning models, and identified high-order radiomics features and regions of abnormal brain activity associated with Parkinson's disease.
FRONTIERS IN AGING NEUROSCIENCE
(2022)
Article
Computer Science, Information Systems
Zichen Zhang, Shifei Ding, Yuting Sun
Summary: This paper introduces a new method called multiple birth support vector regression (MBSVR), which constructs the regressor from multiple hyperplanes obtained by solving small quadratic programming problems, aiming for faster computation and better fitting precision.
INFORMATION SCIENCES
(2021)
Article
Environmental Sciences
Zhihao Wang, Alexander Brenning
Summary: Using active learning with uncertainty sampling can reduce the time and cost needed by experts under limited data conditions, improve model performance, and is particularly suitable for emergency response settings and landslide susceptibility modeling.
Article
Computer Science, Artificial Intelligence
Liming Liu, Maoxiang Chu, Rongfen Gong, Li Zhang
Summary: The improved nonparallel support vector machine (INPSVM) proposed in this article inherits the advantages of nonparallel support vector machine (NPSVM) while also offering incomparable benefits over twin support vector machine (TSVM). INPSVM effectively eliminates noise effects and achieves higher classification accuracy for both linear and nonlinear datasets compared to other algorithms. Experimental results demonstrate the superior efficiency, accuracy, and robustness of INPSVM.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2021)
Article
Materials Science, Multidisciplinary
Wei Zhang, Peiyou Li, Lin Wang, Fangyi Wan, Junxia Wu, Longquan Yong
Summary: Three methods were proposed to explain the different prediction accuracies of a single characteristic parameter in amorphous alloy (AM), solid solution alloy (SS), and high entropy alloy containing intermetallic compound (IM). The first method used simple division to qualitatively explain the high or low prediction accuracies. The second method used histograms of eigenvalues' probability density distribution to explain the accuracies in different regions. The third method involved Gaussian fitting curves of the histograms. The analysis results were consistent with the model learning results.
MATERIALS TODAY COMMUNICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Chen Ding, Tian-Yi Bao, He-Liang Huang
Summary: The study proposes a quantum-inspired classical algorithm for LS-SVM, utilizing an improved sampling technique for classification. The theoretical analysis indicates that the algorithm can achieve classification with logarithmic runtime for low-rank, low-condition number, and high-dimensional data matrices.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2022)
Article
Cardiac & Cardiovascular Systems
Javad Hassannataj Joloudari, Faezeh Azizi, Mohammad Ali Nematollahi, Roohallah Alizadehsani, Edris Hassannatajjeloudari, Issa Nodehi, Amir Mosavi
Summary: This study proposed a hybrid machine learning model called genetic support vector machine and analysis of variance (GSVMA) for diagnosing coronary artery disease (CAD). Through testing on a dataset, it was found that this model achieved the highest accuracy and outperformed other methods. The results demonstrated that support vector machine combined with genetic optimization algorithm could improve the accuracy of CAD diagnosis.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2022)
Article
Computer Science, Information Systems
Ceren Atik, Recep Alp Kut, Reyat Yilmaz, Derya Birant
Summary: This paper proposes a novel method called support vector machine chains (SVMC) that involves chaining together multiple SVM classifiers in a special structure, decrementing one feature at each stage. The paper also introduces a new voting mechanism called tournament voting, where classifiers' outputs compete in groups and the winning class label of the final round is assigned as the prediction. Experimental results show that SVMC outperforms SVM in terms of accuracy and achieves a 6.88% improvement over state-of-the-art methods.
Article
Chemistry, Analytical
Dante Trabassi, Mariano Serrao, Tiwana Varrecchia, Alberto Ranavolo, Gianluca Coppola, Roberto De Icco, Cristina Tassorelli, Stefano Filippo Castiglia
Summary: The aim of this study was to determine the most accurate supervised machine learning algorithm for classifying people with Parkinson's disease from healthy subjects based on gait features. The study found that support vector machine, decision trees, and random forest showed the best classification performances.
Letter
Clinical Neurology
Katsuki Eguchi, Shinichi Shirai, Masaaki Matsushima, Takahiro Kano, Tomohiro Ichikawa, Kazuyoshi Yamazaki, Shuji Hamauchi, Toru Sasamori, Toshitaka Seki, Mayumi Kitagawa, Hideaki Shiraishi, Kiyohiro Houkin, Hidenao Sasaki, Ichiro Yabe
Summary: Our study found a significant reduction in beta-gamma phase amplitude coupling (PAC) values after chronic deep brain stimulation (DBS) in patients with Parkinson's disease, indicating that this reduction is a chronic effect of DBS and not just a transient phenomenon after the start of stimulation.
PARKINSONISM & RELATED DISORDERS
(2021)
Article
Clinical Neurology
Yudthaphon Vichianin, Anutr Khummongkol, Pipat Chiewvit, Atthapon Raksthaput, Sunisa Chaichanettee, Nuttapol Aoonkaew, Vorapun Senanarong
Summary: The study found that using the hippocampus volume as a single feature for brain volumetry had the highest accuracy of 62.64%. Combining clinical parameters as features achieved accuracy between 83 and 90%, while combining brain volumetry and clinical parameters did not improve the accuracy of the results.
FRONTIERS IN NEUROLOGY
(2021)
Letter
Clinical Neurology
Joyce Chelangat Bore, Brett Campbell, Hanbin Cho, Francesco Pucci, Raghavan Gopalakrishnan, Andre Machado, Kenneth Baker
Article
Neurosciences
Raghavan Gopalakrishnan, David A. Cunningham, Olivia Hogue, Madeleine Schroedel, Brett A. Campbell, Ela B. Plow, Kenneth B. Baker, Andre G. Machado
Summary: The robust connections between the cerebellum and contralateral sensorimotor cerebral hemisphere play an important role in human behavior. The reduction of cerebellar metabolism due to damage to the sensorimotor cortex is related to poor rehabilitative outcomes. Understanding the cerebellar physiology and cortico-cerebellar coherence (CCC) after stroke may help in developing techniques for motor rehabilitation. The study found strong coupling between the ipsilesional cortex and the cerebellar dentate nucleus in the low beta band during motor control, supporting the use of the cerebello-thalamo-cortical pathway for neuromodulation.
JOURNAL OF NEUROSCIENCE
(2022)
Article
Multidisciplinary Sciences
Olivia Hogue, Tucker Harvey, Dena Crozier, Claire Sonneborn, Abagail Postle, Hunter Block-Beach, Eashwar Somasundaram, Francis J. May, Monica Snyder Braun, Felicia L. Pasadyn, Khandi King, Casandra Johnson, Mary A. Dolansky, Nancy A. Obuchowski, Andre G. Machado, Kenneth B. Baker, Jill S. Barnholtz-Sloan
Summary: This study rigorously evaluated statistical choices and reporting in published controlled experiments on motor rehabilitation in mice or rats. The majority of articles failed to account for data non-independence and mid-treatment animal attrition, treated ordinal variables as continuous, did not mention outliers, and concealed the distribution of data in plots. Journal rank or reporting requirements did not affect statistical choices and transparency.
Article
Neurosciences
Joyce Chelangat Bore, Carmen Toth, Brett A. Campbell, Hanbin Cho, Francesco Pucci, Olivia Hogue, Andre G. Machado, Kenneth B. Baker
Summary: Parkinson's disease, a neurological disorder characterized by motor symptoms, is found to be associated with changes in network connectivity. The study shows increased power and connectivity in the brain with disease progression, suggesting a possible role of network dysfunction in the manifestation of the disease.
FRONTIERS IN NEUROSCIENCE
(2022)
Article
Medicine, Research & Experimental
Timothy R. Deer, Jason E. Pope, Steven M. Falowski, Julie G. Pilitsis, Corey W. Hunter, Allen W. Burton, Allison T. Connolly, Paul Verrills
Summary: This study retrospectively analyzed clinical data of Medicare beneficiaries who underwent neurostimulator implants in outpatient hospitals, and found that both primary cell (PC) and rechargeable cell (RC) batteries have similar clinical longevity. The assumption that RC batteries have longer battery life has been challenged by this study, and clinicians should consider individual factors when choosing between PC and RC devices.
Article
Family Studies
Matthew D. Johnson, Scott M. Stanley, Galena K. Rhoades
Summary: This study examines whether household income moderates the predictive association between adaptive processes, enduring vulnerabilities, stressors, and future relationship satisfaction. The results suggest that basic longitudinal processes in relationships operate consistently across income level, and income does not moderate the links with future relationship satisfaction.
JOURNAL OF MARRIAGE AND FAMILY
(2023)
Article
Psychology, Clinical
Celine Stadelmann, Mirjam Senn, Fabienne Forster, Valentina Rauch-Anderegg, Fridtjof W. Nussbeck, Matthew D. Johnson, Alexandra Iwanski, Peter Zimmermann, Guy Bodenmann
Summary: How parents cope with stress as a couple is related to child mental health problems. This study found that during the transition to parenthood, most couples experienced a decline in positive coping and an increase in negative coping. If fathers' positive coping declined or parents' negative coping increased, it was associated with more emotional and behavioral problems in children.
JOURNAL OF FAMILY PSYCHOLOGY
(2023)
Article
Psychology, Clinical
Natalie O. Rosen, Sarah A. Vannier, Matthew D. Johnson, Leanne McCarthy, Emily A. Impett
Summary: This longitudinal study found that expectations for sexual relationships have an impact on new parents' sexual and relationship adjustment. Unmet expectations were associated with lower satisfaction and higher distress and conflict, while exceeded expectations were linked to higher satisfaction and lower distress and conflict. These findings highlight the importance of managing expectations during the transition to parenthood.
JOURNAL OF SEX RESEARCH
(2023)
Article
Psychology, Clinical
Rico A. Fischer, Matthew D. Johnson, Anna M. Stertz, Sarah N. Sherlock, Bettina S. Wiese
Summary: This study explores the within-person effect of negative maternal gatekeeping on fathers' weekly reports of romantic relationship quality and feelings of exclusion from the family system. The findings suggest that when fathers perceive more maternal gatekeeping than usual, they experience lower positive romantic relationship quality, higher negative romantic relationship quality, and increased feelings of exclusion from the family system. The study also found that fathers' attachment style, specifically avoidant attachment, moderates the relationship between perceived maternal gatekeeping and negative romantic relationship quality.
JOURNAL OF FAMILY PSYCHOLOGY
(2023)
Review
Psychology, Clinical
Erin. F. F. Alexander, Matthew. D. D. Johnson
Summary: Many theories propose that intimate partner violence (IPV) has distinct types. However, a systematic review of 80 studies testing these typologies found that the number of identified types varied across studies, with the modal number being three. Furthermore, the inconsistency in results casts doubt on the validity and certainty of existing typologies, suggesting caution in using a categorical approach to IPV.
JOURNAL OF FAMILY PSYCHOLOGY
(2023)
Article
Biochemistry & Molecular Biology
Kenneth B. B. Baker, Ela B. B. Plow, Sean Nagel, Anson B. B. Rosenfeldt, Raghavan Gopalakrishnan, Cynthia Clark, Alexandria Wyant, Madeleine Schroedel, John Ozinga, Sara Davidson, Olivia Hogue, Darlene Floden, Jacqueline Chen, Paul J. J. Ford, Lauren Sankary, Xuemei Huang, David A. A. Cunningham, Frank P. P. DiFilippo, Bo Hu, Stephen E. E. Jones, Francois Bethoux, Steven L. L. Wolf, John Chae, Andre G. Machado
Summary: This study investigated the effects of deep brain stimulation combined with physical rehabilitation on upper-extremity impairment in stroke patients. The results showed that deep brain stimulation promoted functional reorganization and improved upper-extremity function. These findings support the use of deep brain stimulation for late-stage neuroplasticity modulation and highlight the need for larger clinical trials.
Article
Family Studies
Quinn E. Hendershot, Matthew D. Johnson
Summary: This review explores the existence of bicultural competence at a dyadic level, where individuals' cultural competence levels determine how effectively they engage with their environment and manage challenges associated with navigating two cultures. The literature on dyadic bicultural competence is limited, particularly in the context of intimate partner relationships, and has yielded mixed findings. The proposed model in this review provides an explanation for these mixed results and can guide future research on the role of cultural competence in migrants' individual and relational functioning.
JOURNAL OF FAMILY THEORY & REVIEW
(2023)
Review
Neurosciences
Jakov Tiefenbach, Leonardo Favi Bocca, Olivia Hogue, Neil Nero, Kenneth B. Baker, Andre G. Machado
Summary: This study evaluated the incidence and risk factors of intracranial bleeding in deep brain stimulation surgery. The results showed that the incidence of intracranial bleeding per each patient was 2.5% and per each implanted lead was 1.4%. Older patients had a higher risk of hemorrhage.
STEREOTACTIC AND FUNCTIONAL NEUROSURGERY
(2023)
Review
Criminology & Penology
Erin F. Alexander, Bethany L. Backes, Matthew D. Johnson
Summary: This article systematically reviewed measures used to identify or predict IPV, assessing their reliability and validity to generate a list of recommended measures. The study also discussed measures designed to differentiate between types of IPV.
TRAUMA VIOLENCE & ABUSE
(2022)
Article
Psychology, Developmental
Marcus Mund, Rebekka Weidmann, Cornelia Wrzus, Matthew D. Johnson, Janina Larissa Buehler, Robert Philip Burriss, Jenna Wuensche, Alexander Grob
Summary: This study suggests that loneliness is associated with relationship satisfaction, conflicts, closeness, and self-disclosure in partner relationships, but not with sexual contact frequency or physical affection.
INTERNATIONAL JOURNAL OF BEHAVIORAL DEVELOPMENT
(2022)