Results 81 to 90 of about 4,044,436 (277)

Argument Mining for Improving the Automated Scoring of Persuasive Essays

AAAI Conference on Artificial Intelligence, 2018
End-to-end argument mining has enabled the development of new automated essay scoring (AES) systems that use argumentative features (e.g., number of claims, number of support relations) in addition to traditional legacy features (e.g., grammar ...
Huy V. Nguyen, D. Litman
semanticscholar   +1 more source

CSF Levels of NPTX2 Are Associated With Less Brain Atrophy Over Time in Cognitively Unimpaired Individuals

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Introduction Neuronal pentraxin 2 (NPTX2) is a synaptic protein involved in synaptic plasticity and regulation of neuronal excitability. Lower baseline cerebrospinal fluid (CSF) NPTX2 levels have been shown to be associated with an earlier onset of mild cognitive impairment (MCI), a pre‐dementia syndrome, even after CSF Alzheimer's Disease (AD)
Juan P. Vazquez, Corinne Pettigrew, Yuxin Zhu, Claire Anderson, Guray Erus, Christos Davatzikos, Michael Miller, Abhay Moghekar, Sungtaek Oh, Chan‐Hyun Na, Marilyn Albert, Paul Worley, Anja Soldan   +12 more
wiley   +1 more source

A Hybrid Automated Essay Scoring Using NLP and Random Forest Regression [PDF]

, 2022
Muhammad Zaim Azri Bin Azahar, Khairil Imran Ghauth   +1 more
openalex   +1 more source

FABRIC: Automated Scoring and Feedback Generation for Essays

arXiv.org, 2023
Jieun Han, Haneul Yoo, Junho Myung, Minsun Kim, Hyunseung Lim, Yoonsu Kim, Tak Yeon Lee, Hwajung Hong, Juho Kim, So-Yeon Ahn, Alice Oh   +10 more
semanticscholar   +1 more source

Automated scoring of the Rey-Osterrieth Complex Figure Test using a deep-learning algorithm

Archives of Clinical Neuropsychology, 2019
To validate a fully automated scoring algorithm for the Rey-Osterrieth Complex Figure Test (ROCFT) by comparing the scoring results of the algorithm to the results of human raters. The algorithm consisted of a cascade of deep neural networks
J. Vogt, H. Kloosterman, S. Vermeent, G. Elswijk, R. Dotsch, B. Schmand   +5 more
semanticscholar   +1 more source

Fibrinogen Changes Before and After Intravenous Thrombolysis as Predictors of Cerebral Injury and Clinical Outcomes in Acute Ischemic Stroke: A Multicenter Prospective Cohort Study

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Plasma fibrinogen is essential in thrombosis and fibrinolysis, yet its dynamic changes pre‐ and post‐intravenous thrombolysis (IVT) for predicting brain injury severity and prognosis in acute ischemic stroke (AIS) patients remain unclear.
Wenhai Zhai, Yang Qu, Reziya Abuduxukuer, Kejia Zhang, Peng Zhang, Xin Tang, Huaimei Zhang, Lijuan Wang, Lichong Yang, Shuangxu Tan, Zhimei Yuan, Ce Han, Lili He, Yuping Zheng, Fenglan Zhao, Lijie Guo, Ligang Jiang, Jinfeng Li, Yongfei Jiang, Xuexia Zou, Dan Xu, Han Xu, Xiaojia Wang, Yingbin Qi, Xuefeng Hu, Yu Zhang, Zhen‐Ni Guo, Hang Jin, on behalf of the Biomarkers of Brain Injury Investigator Study Group   +28 more
wiley   +1 more source

Deep Learning–Assisted Differentiation of Four Peripheral Neuropathies Using Corneal Confocal Microscopy

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Peripheral neuropathies contribute to patient disability but may be diagnosed late or missed altogether due to late referral, limitation of current diagnostic methods and lack of specialized testing facilities. To address this clinical gap, we developed NeuropathAI, an interpretable deep learning–based multiclass classification ...
Chaima Ben Rabah, Ioannis N. Petropoulos, Mark Stettner, Maryam Ferdousi, Uazman Alam, Nathan Efron, Ahmed Serag, Rayaz A. Malik   +7 more
wiley   +1 more source

Post‐COVID Fatigue Is Associated With Reduced Cortical Thickness After Hospitalization

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Neuropsychiatric symptoms are among the most prevalent sequelae of COVID‐19, particularly among hospitalized patients. Recent research has identified volumetric brain changes associated with COVID‐19. However, it currently remains poorly understood how brain changes relate to post‐COVID fatigue and cognitive deficits.
Tim J. Hartung, Florentin Steigerwald, Amy Romanello, Cathrin Kodde, Matthias Endres, Sandra Frank, Peter Heuschmann, Philipp Koehler, Stephan Krohn, Daniel Pape, Jens Schaller, Sophia Stöcklein, Istvan Vadasz, Janne Vehreschild, Martin Witzenrath, Thomas Zoller, Carsten Finke, on behalf of the NAPKON Study Group, Y. Ahlgrimm, C. Finke, J. Fricke, T. Keil, L. Krist, N. Lisewsky, M. Mittermaier, M. Mueller‐Plathe, C. Pley, S. Schmidt, A. Stege, F. Steinbeis, S. Steinbrecher, C. Wildberg, M. Witzenrath, E. Zessin, T. Zoller, C. Arendt, C. Bellinghausen, S. Cremer, A. Groh, A. Gruenewaldt, Y. Khodamoradi, S. Klinsing, G. Rohde, M. Vehreschild, T. Vogl, S. Frank, J. C. Hellmuth, M. Huber, S. Kaeaeb, O. T. Keppler, E. Khatamzas, C. Mandel, S. Mueller, M. Muenchhoff, L. Reeh, C. Scherer, H. Stubbe, M. von Bergwelt, L. Weiss, B. Zwissler, S. Cleef, M. E. Figuera Basso, J. Franzenburg, K. Franzpoetter, A. Friedrichs, A. Hermes, J. Heyckendorf, C. Kujat, I. Lehmann, C. Maetzler, S. Meier, D. Pape, S. Poick, L. Reinke, A. K. Russ, A. M. Scheer, D. Schunk, T. Tamminga, S. Bohnet, D. Droemann, K. F. Franzen, R. Hoerster, N. Kaeding, M. Nissen, P. Parschke, J. Rupp, S. Caesar, H. Einsele, S. Frantz, A. Frey, A. Grau, K. Haas, C. Haertel, K. G. Haeusler, G. Hein, J. Herrmann, A. Horn, R. Jahns, P. Meybohm, F. A. Montellano, C. Morbach, J. Schmidt, P. Schulze, S. Stoerk, J. Volkmann, T. Bahmer, A. Hermes, M. Krawczak, W. Lieb, S. Schreiber, T. Tamminga, B. Balzuweit, S. Berger, J. Fricke, M. Hummel, A. Krannich, L. Krist, F. Kurth, J. Lienau, R. Lorbeer, C. Pley, J. Schaller, S. Schmidt, C. Thibeault, M. Witzenrath, T. Zoller, I. Bernemann, T. Illig, M. Kersting, N. Klopp, V. Kopfnagel, S. Muecke, M. Kraus, B. Lorenz‐Depiereux, G. Anton, A. Kuehn‐Steven, S. Kunze, M. K. Tauchert, K. Appel, M. Brechtel, I. Broehl, K. Fiedler, R. Geisler, S. M. Hopff, K. Knaub, C. Lee, S. Nunes de Miranda, S. Raquib, G. Sauer, M. Scherer, J. J. Vehreschild, P. Wagner, L. Wolf, J. C. Hellmuth, K. Guenther, F. Haug, J. Haug, A. Horn, M. Kohls, C. Fiessler, P. U. Heuschmann, O. Miljukov, C. Nuernberger, J. P. Reese, L. Schmidbauer, I. Chaplinskaya, S. Hanss, D. Krefting, C. Pape, M. Rainers, A. Schoneberg, N. Weinert, T. Bahls, W. Hoffmann, M. Nauck, C. Schaefer, M. Schattschneider, D. Stahl, H. Valentin, P. Heuschmann, A. L. Hofmann, S. Jiru‐Hillmann, J. P. Reese, S. Herold, P. Heuschmann, R. Heyder, W. Hoffmann, T. Illig, S. Schreiber, J. J. Vehreschild, M. Witzenrath   +190 more
wiley   +1 more source

An automated sleep-state classification algorithm for quantifying sleep timing and sleep-dependent dynamics of electroencephalographic and cerebral metabolic parameters

Nature and Science of Sleep, 2015
Michael J Rempe,1,2 William C Clegern,2 Jonathan P Wisor2 1Mathematics and Computer Science, Whitworth University, Spokane, WA, USA; 2College of Medical Sciences and Sleep and Performance Research Center, Washington State University, Spokane, WA ...
Rempe MJ, Clegern WC, Wisor JP
doaj  

Acoustic Measures Capture Speech Dysfunction in Spinocerebellar Ataxia

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Spinocerebellar ataxias (SCA) are hereditary cerebellar degenerative disorders with a common feature of dysarthria, involving impaired phonatory and articulatory control of speech, thereby affecting social communication. In this study, we investigated whether acoustic measures could objectively measure speech dysfunction and identify
Zena Fadel, Charlotte Hennessey, Hannah Lee, Pia Parekh, Sheng‐Han Kuo, Ami Kumar   +5 more
wiley   +1 more source