Search Results - "Quantitative EEG"

Quantitative EEG-Based Regional Spectral Analysis for Parkinson’s Disease Detection

Agrawal, Sneha, Sahu, Satya Prakash

2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI)

Quantitative EEG in Patients with Schizophrenia

Panov, Georgi^{Aff6, Aff7}

Stoyanov, Drozdstoy^Aff2, Draganski, Bogdan^Aff3, Brambilla, Paolo^Aff4, Lamm, Claus^Aff5, Walz, Wolfgang^Aff1

Network Connectivity Measures to Assess Changes in Brain Activity of Stroke Patients

Gutierrez-Martinez, Josefina, Mercado-Gutierrez, Jorge A., Pacheco-Gonzalez, Luis E., Quinzanos-Fresnedo, Jimena, Ramirez-Nava, Ana G., Benitez-Sanchez, Guadalupe, Yanez-Suarez, Oscar

2024 21st International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)

Quantitative electroencephalogram and machine learning to predict expired sevoflurane concentration in infants

Kumar, Rachit, Skowno, Justin^{Aff2, Aff3}, von Ungern-Sternberg, Britta S.^{Aff4, Aff5, Aff6, Aff7}, Davidson, Andrew^{Aff8, Aff9, Aff10}, Xu, Ting, Zhang, Jianmin, Song, XingRong, Zhang, Mazhong^{Aff14, Aff15, Aff16}, Zhao, Ping, Liu, Huacheng^{Aff18, Aff19, Aff20}, Jiang, Yifei, Zuo, Yunxia, de Graaff, Jurgen C.^{Aff23, Aff24}, Vutskits, Laszlo^{Aff25, Aff26}, Olbrecht, Vanessa A.^{Aff27, Aff28}, Szmuk, Peter^{Aff29, Aff30}, Simpao, Allan F., ^{Aff31, Aff32}, Padiyath, Asif, Nelson, Olivia, Kurth, Charles D., Yuan, Ian^{Aff31, IDs10877025013012_cor1}

A Quantitative EEG Signal Analysis Approach for the Evaluation of Neurophysiological Changes Associated with Mesial Temporal Lobe Epilepsy

Bonacci, Maria Celeste, Sammarra, Ilaria, Caligiuri, Maria Eugenia, Sturniolo, Miriam, Martino, Iolanda, Vizza, Patrizia, Veltri, Pierangelo, Gambardella, Antonio

2023 International Workshop on Biomedical Applications, Technologies and Sensors (BATS)

EEG Features in Young Female Patients with Depressive States at Different Stages of Endogenous Mental Disorders

Iznak, A. F.^{Aff1, IDs1105502501796x_cor1}, Iznak, E. V., Damyanovich, E. V., Shishkovskaya, T. I., Oleichik, I. V.

Early Burst Suppression Similarity Association with Structural Brain Injury Severity on MRI After Cardiac Arrest

Shivdat, Shawn^{Aff1, Aff2}, Zhan, Tiange, De Palma, Alessandro^{Aff3, Aff4}, Zheng, Wei-Long, Krishnamurthy, Parimala, Paneerselvam, Ezhil, Snider, Samuel, Bevers, Matthew, O’Reilly, Una-May, Lee, Jong Woo^{Aff2, Aff7}, Westover, M. Brandon^{Aff2, Aff8}, Amorim, Edilberto^{Aff2, Aff3, Aff9, IDs12028024020476_cor1}

Comparison of Feature Engineering and End-to-End Machine Learning for Neonatal Preictal State Classification

Kim, Jonathan^Aff8, Glass, Hannah C.^{Aff9, Aff10, Aff11}, Amorim, Edilberto^Aff9, Rao, Vikram R.^Aff9, Bernardo, Danilo^Aff9

Li, Gang, Series Editor^Aff1, Filipe, Joaquim, Series Editor^Aff2, Xu, Zhiwei, Series Editor^Aff3, Ehwerhemuepha, Louis, editor^Aff4, Hoffman, Mark, editor^Aff5, Kalawi, Adam, editor^Aff6, Sanger, Terence, editor^Aff7

Neural correlates of β-lactam exposure in intensive care unit patients: an observational, prospective cohort study

Zalta, Arnaud^{Aff1, Aff2, IDs00415025130673_cor1}, Trébuchon, Agnès^{Aff1, Aff3}, Daquin, Géraldine, Velly, Lionel^{Aff4, Aff5}, Leone, Marc, Blin, Olivier^{Aff1, Aff2}, Lagarde, Stanislas^{Aff1, Aff3}, Guilhaumou, Romain^{Aff1, Aff2}

Explainable machine learning model based on EEG, ECG, and clinical features for predicting neurological outcomes in cardiac arrest patient

Yanxiang Niu, Xin Chen, Jianqi Fan, Chunli Liu, Menghao Fang, Ziquan Liu, Xiangyan Meng, Yanqing Liu, Lu Lu, Haojun Fan

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Standardized low-resolution brain electromagnetic tomography does not improve EEG Alzheimer's disease assessment

Wolfgang Frühwirt, Martin Mairhofer, Andreas Hahn, Heinrich Garn, Markus Waser, Reinhold Schmidt, Thomas Benke, Peter Dal-Bianco, Gerhard Ransmayr, Dieter Grossegger, Stephen Roberts, Georg Dorffner

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Background EEG Suppression Ratio for Early Detection of Cerebral Injury in Pediatric Cardiac Arrest

Sansevere, Arnold J.^{Aff1, Aff2, Aff3, IDs12028023019200_cor1}, Janatti, Ali^{Aff1, Aff2}, DiBacco, Melissa L.^{Aff1, Aff2}, Cavan, Kelly^{Aff1, Aff2}, Rotenberg, Alexander^{Aff1, Aff2}

Differentiating neurodegenerative diseases based on EEG complexity

Giovanni Mostile, Roberta Terranova, Giulia Carlentini, Federico Contrafatto, Claudio Terravecchia, Giulia Donzuso, Giorgia Sciacca, Calogero Edoardo Cicero, Antonina Luca, Alessandra Nicoletti, Mario Zappia

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Quantitative EEG Feature Selection by MajorityVoting for Alcohol Use Disorder Detection

Holker, Ruchi, Susan, Seba

2021 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI)

Linear Monotonic Inter-electrode Associations as Quantitative EEG for Alcoholism Diagnosis

Holker, Ruchi^{Aff1, IDs4419602400660z_cor1}, Susan, Seba

Quantitative electroencephalography predicts delayed cerebral ischemia after aneurysmal subarachnoid hemorrhage: a retrospective study

Xu, Mengyuan ^{a, 1}, Zhang, Pengzhao ^{b, 1}, Liu, Yang ^c, Zhang, Jiaqi ^d, Feng, Guang ^{e, ⁎}, Han, Bingsha ^{e, ⁎}

Entropy, complexity, and spectral features of EEG signals in autism and typical development: a quantitative approach

Aleksandar Tenev, Silvana Markovska-Simoska, Andreas Müller, Igor Mishkovski

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Quantitative Electroencephalography in Term Neonates During the Early Postnatal Period Across Various Sleep States

Zhang R, Dong X, Zhang L, Lin X, Wang X, Xu Y, Wu C, Jiang F, Wang J

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Electroencephalographic Features of Alcohol Use Disorders with Different Decision-Making Efficiency in Risk Conditions

Galkin, S. A.^{Aff1, IDS0362119724700725_cor1}

Quantitative electroencephalogram in term neonates under different sleep states

Yuan, Ian^{Aff1, IDs10877023010826_cor1}, Georgostathi, Georgia, Zhang, Bingqing, Hodges, Ashley, Kurth, C. Dean, Kirschen, Matthew P., Huh, Jimmy W., Topjian, Alexis A., Lang, Shih-shan^{Aff4, Aff5}, Richter, Adam^{Aff2, Aff6}, Abend, Nicholas S.^{Aff1, Aff5, Aff7}, Massey, Shavonne L.^{Aff5, Aff7}