Ensemble approach for detection of depression using EEG features
iCV Lab, University of Tartu（塔尔图大学 iCV 实验室）；Biosignal Processing Laboratory, Tallinn University of Technology（塔林理工大学生物信号处理实验室）；Yildiz Technical University（耶尔德兹技术大学）
Depression is a public health issue which severely affects one's well being and cause negative social and economic effect for society. To rise awareness of these problems, this publication aims to determine if long lasting effects of depression can be determined from electoencephalographic (EEG) signals. The article contains accuracy comparison for SVM, LDA, NB, kNN and D3 binary classifiers which were trained using linear (relative band powers, APV, SASI) and non-linear (HFD, LZC, DFA) EEG features. The age and gender matched dataset consisted of 10 healthy subjects and 10 subjects with depression diagnosis at some point in their lifetime. Several of the proposed feature selection and classifier combinations reached accuracy of 90% where all models where evaluated using 10-fold cross validation and averaged over 100 repetitions with random sample permutations.
Incomplete Depression Feature Selection with Missing EEG Channels
Beijing University of Technology, Beijing, China（北京理工大学）；Anhui University, Hefei, China（安徽大学）；North China Electric Power University, Beijing, China（华北电力大学）
Brunel University London（伦敦布鲁内尔大学）；Technical University of Darmstadt（达姆施塔特工业大学）；American International University-Bangladesh（孟加拉国国际大学）；Dhaka University of Engineering and Technology（达卡工程技术大学）；George Mason University（乔治梅森大学）
Transfer entropy applied on EEG in depression reveals aberrated dynamics
Instituto de Tecnología del Conocimiento, Universidad Complutense de Madrid（马德里康普顿斯大学知识技术学院）；TomTom（TomTom公司）；Institute for Experimental Phonetics and Speech Pathology（实验语音学与言语病理学研究所）；Research and Development Institute – Life Activities Advancement Center（生活活动促进中心研发所）
EEG machine learning with Higuchi fractal dimension and Sample Entropy as features for successful detection of depression
University of Belgrade（贝尔格莱德大学）；Amsterdam Health and Technology Institute, HealthInc（阿姆斯特丹健康与技术研究所）；Delaware State University（特拉华州立大学）；Life Activities Advancement Center（生命活动促进中心）；Institute for Experimental Phonetics and Speech Pathology（实验语音学与言语病理学研究所）；Institute for Mental Health（精神卫生研究所）；College of Medicine and Health Sciences, UAE University（阿联酋大学医学与健康科学学院）
Time-Resolved EEG Decoding of Semantic Processing Reveals Altered Neural Dynamics in Depression and Suicidality
Alfred E. Mann Department of Biomedical Engineering, University of Southern California（阿尔弗雷德·E·曼生物医学工程系，南加州大学）；Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California（明世系电气与计算机工程系，南加州大学）；Thomas Lord Department of Computer Science, University of Southern California（托马斯·洛德计算机科学系，南加州大学）；Brain and Creativity Institute, University of Southern California（创造力与大脑研究所，南加州大学）；Department of Psychology, University of Southern California（心理学系，南加州大学）；Information Science Institute, University of Southern California（信息科学研究所，南加州大学）；Department of Psychiatry and Behavioral Sciences, University of Southern California（精神病学与行为科学系，南加州大学）；Department of Psychology, University of California, Los Angeles（心理学系，加州大学洛杉矶分校）；Department of Linguistics, University of Southern California（语言学系，南加州大学）
Beyond Augmentation: Score-Guided Pathological Prior for EEG-based Depression Detection
School of Internet, Anhui University（安徽大学互联网学院）；School of Computer Science and Technology, Hefei University of Technology（合肥工业大学计算机科学与技术学院）；School of Computer Science and Information Engineering, Hefei University of Technology（合肥工业大学计算机科学与信息工程学院）
Graph Learning for Cross-Subject, Cross-Population EEG Emotion Decoding and Model-Derived Spatial-Spectral Neural Signatures
Chongqing University of Technology（重庆理工大学）；The Hong Kong Polytechnic University（香港理工大学）；Chongqing Polytechnic University of Electronic Technology（重庆电子工程职业技术大学）；Affiliated Lianyungang Hospital of Xuzhou Medical University（徐州医科大学附属连云港医院）
Ensemble Feature Selection and Harris Hawks Optimization for Explainable Mental Health Risk Prediction in Female Sex Workers
Department of Information Sciences and Technology（信息科学与技术系）；George Mason University（乔治·马歇尔大学）；Department of Computer Science and Engineering（计算机科学与工程系）；Jahangirnagar University（贾汗吉尔纳加尔大学）；AIUB；The University of Texas at Dallas（德克萨斯大学达拉斯分校）；Dhaka University of Engineering and Technology（达卡工程与技术大学）
EEG based Major Depressive disorder and Bipolar disorder detection using Neural Networks: A review
COMSATS University Islamabad（伊斯兰堡COMSATS大学）；University of Okara（奥卡拉大学）；Ca’ Foscari University of Venice（威尼斯大学）；Ege University（埃格大学）；Université Paris-Est Créteil (UPEC)（巴黎东克雷泰伊大学（UPEC））
QuanvNeXt: An end-to-end quanvolutional neural network for EEG-based detection of major depressive disorder
The University of Queensland（昆士兰大学）；BRAC University（布拉克大学）；Bangladesh Medical University（孟加拉医学大学）；University of Southern Queensland（南方昆士兰大学）；Charles Sturt University（查尔斯·斯特劳特大学）
A Model-Mediated Stacked Ensemble Approach for Depression Prediction Among Professionals
Associate Professor Department of Mathematics American International University-Bangladesh Dhaka, Bangladesh（副教授 数学系 美国国际大学-孟加拉国 达卡, 孟加拉国）；Undergraduate Student Department of Computer Science American International University-Bangladesh Dhaka, Bangladesh（本科生 计算机科学系 美国国际大学-孟加拉国 达卡, 孟加拉国）；Lecturer Department of Computer Science（讲师 计算机科学系）；Computer Science Department King Fahd University of Petroleum（计算机科学系 拜耶德国王石油和矿物大学）
Isomorphic Functionalities between Ant Colony and Ensemble Learning: Part III -- Gradient Descent, Neural Plasticity, and the Emergence of Deep Intelligence
School of Mathematics and Statistics, Rochester Institute of Technology（罗彻斯特理工学院数学与统计学院）；Gosnell School of Life Sciences, Rochester Institute of Technology（罗彻斯特理工学院戈斯内尔生命科学学院）；Center for Imaging Science, Rochester Institute of Technology（罗彻斯特理工学院成像科学中心）
Enhancing Robustness of Asynchronous EEG-Based Movement Prediction using Classifier Ensembles
Robotics Innovation Center（机器人创新中心）；German Research Center for Artificial Intelligence (DFKI)（德国人工智能研究中心）；Institute of Medical Technology Systems（医疗技术系统研究所）；University of Duisburg-Essen（杜伊斯堡- Essen大学）
High Frequency EEG Artifact Detection with Uncertainty via Early Exit Paradigm
University of Cambridge（剑桥大学）；The Alan Turing Institute（艾伦·图灵研究所）
脑电图（EEG）是监测和诊断大脑疾病的关键。然而，EEG信号遭受由非大脑伪影引起的扰动，限制了它们的功效。当前的伪影检测管道是资源消耗型的，并且严重依赖于手工制作的功能。此外，这些管道本质上是确定性的，使它们无法捕获预测的不确定性。我们提出了E4G，一个用于高频EEG伪影检测的深度学习框架。我们的框架利用了早期退出范式，建立了一个能够捕捉不确定性的隐式模型集合。我们评估了我们的方法在天普大学医院EEG语料库（v2.0）实现国家的最先进的分类结果。此外，E4G提供了良好校准的不确定性指标，可与抽样技术（如Monte Carlo dropout）相媲美。E4G为支持临床医生在环框架的不确定性感知伪影检测打开了大门。
Ensemble learning using individual neonatal data for seizure detection
University of Iceland（冰岛大学）；Kvikna Medical ehf.（Kvikna医疗公司）；Helsinki University Hospital（赫尔辛基大学医院）；University of Helsinki（赫尔辛基大学）；QIMR Berghofer Medical Research Institute（QIMR伯格霍费尔医学研究所）
TF-MCL: Time-frequency Fusion and Multi-domain Cross-Loss for Self-supervised Depression Detection
Tianjin University（天津大学）；Nanchang Police Dog Base of the Ministry of Public Security（公安部南昌警犬基地）；Jiangxi Provincial Key Laboratory of Police Dog Breeding and Behavioral Science（江西省警犬繁育与行为科学重点实验室）
T-TIME: Test-Time Information Maximization Ensemble for Plug-and-Play BCIs
Huazhong University of Science and Technology（华中科技大学）；School of Artificial Intelligence and Automation（人工智能与自动化学院）；Shenzhen Huazhong University of Science and Technology Research Institute（华中科技大学深圳研究院）；Zhengzhou University（郑州大学）；School of Electrical and Information Engineering（电气工程学院）；School of Civil and Hydraulic Engineering（土木工程与水利工程学院）
M3D: Manifold-based Domain Adaptation with Dynamic Distribution for Non-Deep Transfer Learning in Cross-subject and Cross-session EEG-based Emotion Recognition
School of Biomedical Engineering, Medical School, Shenzhen University（生物医学工程学院，医学学院，深圳大学）；School of Public Health, Shenzhen University Medical School（公共卫生学院，深圳大学医学学院）；Department of Radiology, Nanshan Hospital of Shenzhen University（放射科，深圳大学南山医院）；School of Mathematical Sciences, Shenzhen University（数学科学学院，深圳大学）；Shien-Ming Wu School of Intelligent Engineering, South China University of Technology（申明武智能工程学院，华南理工大学）；Institute for Super Robotics, Guangzhou, Guangdong, China（超机器人研究所，广州，广东，中国）
Convolutional Neural Networks for Sleep Stage Scoring on a Two-Channel EEG Signal
University of A Coruna（拉科鲁尼亚大学）；Instituto de Investigacion Biomedica de A Coruña (INIBIC)（拉科鲁尼亚生物医学研究所）；Complexo Hospitalario Universitario de A Coruña (CHUAC)（拉科鲁尼亚大学医院）
Albert-Ludwigs-University Freiburg（弗莱堡阿尔伯特-路德维希大学）；Motol University Hospital, Charles University Prague（布拉格查理大学莫托尔大学医院）；University Medical Center Freiburg（弗莱堡大学医学中心）
EMOTHAW: A novel database for emotional state recognition from handwriting
CNRS（法国国家科学研究中心）；Second University of Naples（那不勒斯第二大学）；International Institute for Advanced Scientific Studies-IIASS（国际高级科学研究院-IIASS）；Escola Universitaria Politecnica de Mataro（马塔罗理工学院）；TecnoCampus Mataro-Maresme（马塔罗-马雷斯梅技术园区）
