Team name Entry ID Submission ID Title Team members Programming language Session Accepted CinC abstract? Wild card CinC abstract? Withdrawn CinC abstract? Withdrawn from Challenge? CinC preprint uploaded by deadline? Successful unofficial phase entry Successful official phase entry before July 7, e.g., if no successful unofficial phase entry? Successful official phase entry? Working code, i.e., scored on the validation set in the official phase? Had an entry from the official phase that scored on the training, validation, and test sets? Robust code, i.e., had a final entry from the official phase that passes experiment with modified training set? Final CinC paper accepted by deadline? Eligible for rankings and prizes? AHU lab 2297 144 A Neurological Recovery Prediction Algorithm based on Multi-Feature Selection and Deep Bagging Aggregation ke jiang Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE AIA N/A 168 Predicting Neurological Recovery from Coma Post Cardiac Arrest Using Machine Learning Alireza Tavakolian, Hamid Reza Masoudi Sani Jouybari, Javaher Nourian, Amirhossein Zobeiri, Alireza Moslem Yazdi, Farshid Hajati, Alireza Rezaee, Alireza Rafiei Python N/A FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE AIMED 2259 165 Developing a Machine Learning Pipeline for Predicting Neurological Outcomes in Comatose Cardiac Arrest Survivors Using Continuous EEG Data Quenaz Bezerra Soares, Felipe Meneguitti Dias, Estela Ribeiro, Jose Eduardo Krieger, Marco Gutierrez Python S62-3 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE Aircas 2627 88 Predicting Neurologic Recovery of Cardiac Arrest Patients Using Long-Term EEG Recordings Based on Graph Neural Network Siying Li, Yonggang Zou Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE AIrhythm 2510 142 Neurological Outcome Prediction in Comatose Cardiac Arrest Patients Using EEG Expert Features Morteza Zabihi, Alireza Chaman Zar, Pulkit Grover, Eric S. Rosenthal Python S62-4 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE am_vision 2465 236 Hybrid Feature Fusion with CNN for Predicting Prognosis of Postanoxic Comatose Patients Bharadwaj Madiraju, Sushanth Dondapati, Subhash khambampati, Chaithanya Kalyan Reddy Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE Apnea-ai 2138 20 Convolutional Transformer for Neurological Outcome Prediction after Cardiac Arrest Lampros Kokkalas, Nicolas A. Tatlas, Stelios M. Potirakis Python N/A TRUE FALSE TRUE FALSE FALSE TRUE FALSE TRUE TRUE TRUE FALSE FALSE FALSE Ara N/A N/A N/A Araivndh Palaniappan Python N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE BioITACA_UPV N/A 364 Frequency Microstates as a Novel Approach to Classify Cerebral Performance of Comatose Patients After Cardiac Arrest Rafael Teodoro Ors Quixal, Jose Millet Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE BJUT-bme 2192 49 Predicting Neurological Recovery from Coma After Cardiac Arrest With Multiscale Deep Neural Networks GAO MENG Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE FALSE Blue and Gold 2343 442 A Dynamical Systems Approach to Predicting Patient Outcome after Cardiac Arrest Team: Blue and Gold Richard Povinelli, Matthew DuPont, David Kaftan Python P7_8 TRUE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE Brainary 2329 11 Novel Methods for Predicting Neurological Recovery from Coma After Cardiac Arrest by Utilizing the Dominant Information Flow in Multi-channel EEGs kabmun cha, taeyoun Kim, joung bae Choi MATLAB R2023a P7_8 TRUE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE FALSE FALSE BrainExplore N/A 325 Development of a model for estimation of the prognosis of cardiac arrest outcome Mariana Cardoso Melo, Dharmendra Gurve MATLAB R2022b N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE BrAInstorm 2517 210 Combining Established and Novel EEG Features for Prediction of Secondary Neurologic Outcome After Cardiac Arrest Philip Zaschke, Philip Gemke, Miriam Goldammer, Nicolai Spicher Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE BrownBAI N/A 308 Leveraging Unlabeled Electroencephalographic Data to Predict Neurologic Recovery After Cardiac Arrest Isaac Sears, Augusta Garcia-Agundez, George Zerveas, William Rudman, Laura Mercurio, Adeel Abbasi, Carsten Eickhoff Python S52-3 TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE Buckeye AI 2180 N/A N/A Ping Zhang, Rahul Mukthineni, Jana Abedeljaber Python N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE FALSE Cerenion N/A 96 Computationally Efficient Early Prognosis of the Outcome of Comatose Cardiac Arrest Survivors Using Slow-Wave Activity Features in EEG Miikka Salminen, Juha Partala, Eero V√§yrynen, Jukka Kortelainen Python S62-2 TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE CeZIS 2450 303 Predicting Neurological Recovery From Coma Using Self-Supervised Learning on Electroencephalograms Peter Bugata, Peter Bugata Jr., David Gajdos, David Hudak, Vladimira Kmecova, Monika Stankova, Lubomir Antoni, Erik Bruoth, Simon Horvat, Alexander Szabari, Gabriela Vozarikova, Ivan Zezula Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE FALSE FALSE FALSE CHY N/A N/A N/A 花昌诚, 陈启思, 喻恒 Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE coma-nication N/A 82 Prediction for Neurologic Prognostication of Comatose Patients based on Spectral Features from Electroencephalogram Jae-Man Shin, Sung-Hoon Kim Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE ComaKarma_AMC N/A 427 Predicting Neurologic Outcome of Cardiac Arrest Patients Using Wavelet-Based Electroencephalogram Features Keewon Shin Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE ComaToast 2499 255 Machine Learning Approach for Outcome Prediction in Postanoxic Coma Patients Using Frequency Domain Features Vijay Vignesh Venkataramani, Akshit Garg, U. Deva Priyakumar Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE ComaToss 2577 77 EEG Signal Quality Filtering for Improved Prediction of Neurological Outcome after Cardiac Arrest Dong-Kyu Kim Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE CQUPT_FP_mana 2178 99 MMCTNet: Multi-Modal Conv-Transformer Network for Predicting Good and Poor Outcomes in Cardiac Arrest Patients Shizhan Tang, Zonglin Yang Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE CQUPT_MH_Team N/A 279 Transformer embedded with Double-layer Full Connected Neural Network for brain wave detection ˵´ È©¨, Luyang Ren, Wei Lu Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE TRUE TRUE FALSE FALSE CVGJ N/A 41 Embed and Classify‚Äî Leveraging recent Deep Learning developments to predict patient outcomes after cardiac arrest. Gideon Stein, Tim Buechner, Felix Schneider, Maria Gogolev, Yuxuan Xie Python N/A TRUE FALSE TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE Data Doctors 2124 297 A Mixed Nonstationary Outcome Prediction Model of EEG for Comatose Patients after Heart Attack Shuaixun Wang, Siyi Liu, Martyn G. Boutelle Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE DEIB_POLIMI 2324 372 Predicting Comatose Patient’s Outcome Using Brain Functional Connectivity with a Random Forest Model Cristian Drudi, Inês Sampaio, Jiaying Liu, Ricardo Coimbra Brioso, Anna Maria Bianchi, Riccardo Barbieri, Luca Mainardi Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE dreamer N/A N/A N/A 赵皓楠, 薛纪航, Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE Edinburgh_AN 2467 365 Machine Learning-based Prediction of Neurological Recovery in Cardiac Arrest Patients using EEG: A Multi-centre Study Arjita Nema, Syed Ahmar Shah Python N/A TRUE FALSE TRUE FALSE FALSE TRUE FALSE TRUE FALSE FALSE FALSE FALSE FALSE EEG pz lmn sqz 2394 48 Prediction Comatose Patient Outcomes Using Deep learning-based Analysis of 72-Hour EEG Power Spectral Density KYUNG MIN CHOI, Giwon Yoon, sanghoon CHOI, Hyeon-Hwa Choi, Segyeong Joo Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE EEG-Attackers 2273 133 MemoryInception: Predicting Neurological Recovery from EEG using Recurrent Inceptions Bjørn-Jostein Singstad, Jesper Ravn, Arian Ranjbar Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE EEGnition 2422 422 Outcome Prediction after Cardiac Arrest using Machine Learning and Network Dynamics of Resting-State Electroencephalography Charlotte Maschke, Beatrice De Koninck, Kira Dolhan, Miriam Han, Stefanie Blain-Moraes Python S52-5 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE eHealth NSW N/A 290 Prediction of Cardiac Arrhythmia prognosis from EEG signals using Bidirectional LSTM Rishad Katrak, Andrew Ponce N/A P7_8 TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE ELTE-SP-Lab 2175 198 Enhancing Neurological Recovery Prediction through Knowledge-Augmented Deep Learning Adam Vajda, Peter Kovacs Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE EPOCA 2511 335 Neurological Outcome Prediction in Coma after Cardiac Arrest Using Electroencephalography Based CAE-LSTM Modeling Sterre de Jonge, Maritta N. van Stigt, Eva A. Groenendijk, Kika B. Banning, Loes J. S. C. Gennissen, Brian S. Doelkahar, Anne-Fleur van Rootselaar Python N/A TRUE FALSE TRUE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE FINDING_MEMO 2078 458 Predicting Neurological Outcomes in Comatose Cardiac Arrest Patients Using Transformer Neural Networks with EEG Data Jefferson Dionisio, Che Lin, Lian-Yu Lin, Wen-Chau Wu Python P7_8 FALSE TRUE FALSE FALSE TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE FMMGroup_UVa 2113 102 FMM Features and Machine Learning for Predicting Neurological Recovery from Coma After Cardiac Arrest: The George B. Moody PhysioNet Challenge 2023 Christian Canedo, Adolfo Fern√°ndez-Santam√≥nica, Itziar Fern√°ndez, Yolanda Larriba, Cristina Rueda Python S52-4 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE GU_HIDS_LoneWolf N/A 78 Using Clinical Features and Electroencephalogram Data to Predict Future Outcomes in Cardiac Arrested Patients Adam Li Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE HeartsAndMinds 2484 278 Variational Autoencoders for Electroencephalogram Feature Extraction in Patients with Coma after Cardiac Arrest Adel Hassan, Liam Ferreira Python P7_8 TRUE FALSE FALSE FALSE TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE FALSE ibmtPeakyFinders 2518 57 Assessing Brain Dynamics for Predicting Postanoxic Coma Recovery: An EEG Based Approach Marc Goettling, Franz Ehrlich, Richard Hohmuth, Hannes Ernst, Alexander Hammer, Matthieu Scherpf, Martin Schmidt Python S62-1 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE IIS 2419 65 Automated Analysis of EEG Signals for Early Diagnosis of Severe Brain Injury following Cardiac Arrest using Contrastive Pretraining and Expert Features Maximilian Oppelt, Andreas Foltyn, Anne-Marie Strauch, Felix Kemeth, Nadine Lang-Richter Python N/A TRUE FALSE TRUE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE ISIBrno-AIMT N/A 54 Utilization of CNN embedding extractactor and Transformer encoder for predicting neurological recovery from coma based on EEG Jan Pavlus, Kristyna Pijackova, Zuzana Koscova, Radovan Smisek, Ivo Viscor, Vojtech Travnicek, Petr Nejedly, Filip Plesinger Python S52-2 TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE IWillSurvive N/A 173 Transformer Network with Time Prior for Predicting Clinical Outcome from EEG of Cardiac Arrest Patients Maurice Rohr, Tobias Schilke, Laurent Willems, Sebastian Dill, G√∂khan G√ºney, Christoph Hoog Antink Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE khuBME N/A N/A N/A Jina Lee, Juhyun Jun, Lim Dong Kyu, Jinseok Lee Python N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE klabs N/A N/A N/A Winston Zhang Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE Kycosu N/A 239 Team Kycosu: Neurological Recovery Prediction from EEG using a Cascaded Model Daniel Kyrollos, Martin S. Copenhaver, Christopher Sun Python N/A TRUE FALSE TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE L_L N/A 147 Using Deep Neural Networks to Predict Neurological Recovery of Comatose Patients after Cardiac Arrest jianqiang Liu, yingdian Li Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE Labio_YH N/A 118 Prognostic Analysis of Comatose Patients' EEG based on Adaptive ViT Yiming Han Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE Leicester Fox 2617 394 Predicting Cardiac Arrest Recovery with Shallow and Deep Learning Models Ekenedirichukwu Obianom, Marko M√§kynen, NOOR QAQOS, Shamsu Idris Abdullahi, Fernando Schlindwein, G Andr√© Ng, Xin Li MATLAB R2022b, MATLAB R2023a P7_8 TRUE FALSE FALSE FALSE TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE FALSE MARTA 2020 318 Comatose Patient Electroencephalogram Processing with a Synchrosqueezing Convolutional Transformer Ed Jaras MATLAB R2023a P7_8 TRUE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE FALSE MBSI N/A 284 Integrated approach to predicting post-cardiac arrest outcome using EEG pattern identification and convolutional neural networks Allen Gu, Po Liu Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE Medics 2229 314 A tensor decomposition-based feature extraction method to predict neurological recovery from coma after cardiac arrest using EEG signals Shivnarayan Patidar, Nidhi Sawant Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE Melody N/A N/A N/A N/A Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE MetaHeart_YNNU 2439 14 Predicting Neurological Outcome for Cardiac Arrest Patients from Long-Term EEG Based on Convolutional Neural Networks and Multi-Scale Transformer Yusi Zhu Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE MIWEAR 2562 84 Machine Learning for EEG-based Prognostication after Cardiac Arrest Wenlong Wu, Ying Tan Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE ML_Explorer N/A 419 1D Self-ONNs for predicting neurological recovery after cardiac arrest Muhammad Uzair Zahid Python N/A TRUE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE ModelExplorer N/A N/A N/A Raghav Rao Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE MSU_BMW_lab N/A 139 Cardiac Arrest Recovery Prognosis Estimation Using an Applied Transformer Architecture Isaac Boyd, Bradley M. Whitaker Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE MZR_UA N/A 404 EEG Based Recovery Prediction by convLSTM and XGBoost Muhammad Zoraiz Ramay, Muhammad Usman Akram Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE NAIL_Freiburg 2575 130 Deep Neural Networks for the Prediction of Neurological Recovery after Cardiac Arrest Daniel Wilson, Robin Schirrmeister, Lukas Gemein, Ricardo Licona Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE NeuralRhythms N/A 299 Attention-Based Deep Multiple Instance Learning for Predicting Neurological Recovery of Comatose Cardiac Arrest Patients Using EEG Data Gihun Joo, Minji Roh, Sungkyu Park, Hyeonseung Im Python N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE NeuTech_XJTLU 2464 228 Seeing The Whole Through a Part: Enhancing 2D-CNN for Predicting Neurological Recovery Outcome by Slicing Long-Time-Scale EEG Signals Chenchen Quan, Yi Ni, Xujia Ning, Kaicheng Liang, Yang Bai, Erick Purwanto, Ka lok Man Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE NitWITs N/A 440 Prediction of recovery of post cardiac arrest comatose patients using EEG signal processing and deep learning models Lakshmi Venkatesh Rasineni, Gaurang Prabhudesai, Shanmukha Sai Penumatsa, Manasa Nandimandalam, Youakim Badr, Elie Sarraf Python P7_8 TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE NMI_LEI N/A N/A N/A Sophie Adama MATLAB R2023a N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE Noam N/A 262 Sequential Multi-Resolution Analysis of EEG data for Outcome Prediction Noam Finkelstein Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE NTHU_SereneDream N/A 310 Prediction of Recovery from Coma Following Cardiac Arrest Using Spatio-Temporal LSTM-Based Neural Network Audrey Suhadinata, Kevin Richardson Halim Python N/A TRUE FALSE TRUE TRUE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE Oldenburg 2083 125 Predicting Recovery from Coma After Cardiac Arrest Using EEG Recordings and a CNN-LSTM Network Benjamin Cauchi, Marco Eichelberg, Andreas Hein Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE OPPO_Health_DS N/A 296 Predicting Neurological Recovery from Coma After Cardiac Arrest: A Deep Learning Approach Leveraging Spatio-Temporal EEG Features Xiaoyu Li, Cheng Bian, Guangpu Zhu, Ramy Hussein Python N/A TRUE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE osu_cse_team_2 2133 N/A N/A Zachary Dobos, Jackson Bean, Melanie Qin, Harry Liu Python N/A FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE FALSE FALSE OUS_IVS 2205 251 A Multi-channel EEG Data Analysis with a Channel-wise and Cross-channel Attention Mechanism Hemin Qadir, Naimahmed Nesaragi, Ilnagko Balasingham, Per Steinar Halvorsen Python P7_8 TRUE FALSE FALSE FALSE TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE FALSE PA_HB N/A 21 Neurological Recovery Prediction from Clinical Features and Continuous EEGs: A Multimodal Approach Zhuoyang Xu Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE PandaWarrior 2017 356 Prediction of Prognosis from Longitudinal EEG Recordings using a Long Short-Term Memory-Based Model Kevin Kirmansjah Python N/A FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE FALSE FALSE PES_OC N/A 309 Enhancing Prognostic Accuracy for Comatose Cardiac Arrest Patients through Machine Learning Shubangi Saxena, Shria Guntunur, Shreya Varma, Supreeta Sagere Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE PKU_NIHDS 2538 183 An Ensemble Classifier for Neurological Recovery Prediction Combining Expert Features and Deep Neural Networks Songchi Zhou, Jun Li, Deyun Zhang, Shijia Geng, Ziqian Xie, Chuandong Cheng, Shenda Hong Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE Revenger 2393 60 Predicting Neurological Recovery from Coma with Longitudinal Electroencephalogram Using Deep Neural Networks Jingsu Kang, Hao WEN Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE ROSCy Business N/A 159 Predicting Neurological Recovery of Comatose Patients from Longitudinal EEG Using Recurrent Networks and VAEs for Interpolation of Missing Data Sara Summerton, Benjamin Keel, Samuel Relton, David C. Wong Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE RPG@IISC 2496 188 Deep-Learning-Assisted Prediction of Neurological Recovery from Coma After Cardiac Arrest [PhysioNet Challenge 2023] Vasanth B, Navneet Roshan, Rahul Pandit Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE SD-DataSurfers N/A 191 Multi-Channel EEG-based Cardiac Arrest Outcome Prediction with Machine Learning Po-Ya Hsu, Chi-Yuan Chang Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE SHE Lab N/A 181 A Temporal-Spectral Based Single-lead Electroencephalogram Feature Fusion Network may Provide Potential Clinical Biomarker for Cardiac Arrest Zhaoyang Cong, Minghui Zhao, Feifei Chen, Li Ling, Lukai Pang, Keming Cao, Jianqing Li, Chengyu Liu Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE sparty-23 N/A N/A N/A Sukruth Rao Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE Surv_to_End 2141 N/A N/A Xiaobin Shen Python N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE FALSE swanseacsvision N/A N/A N/A Vasiles Balabanis, Suraj Ramchand, Alex Milne, Fergus Pick, Harry Mason, Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE SwarthBeat 2483 260 An Optimization Approach to EEG Feature Extraction for the Prediction of Neurological Outcome Allan Moser, Jackie Le, Lys Kang MATLAB R2022b, MATLAB R2023a P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE Team KU N/A 23 Quantifying Neurological Recovery in Resource-Restricted Environments with Random Forest Mostafa Moussa, Hessa I. Alfalahi, Mohanad Alkhodari, Leontios Hadjileontiadis, Ahsan Khandoker MATLAB R2023a P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE FALSE TEAM_NEURO_KGP N/A 361 Identifying Electroencephalogram Biomarkers for Automated Prognostics after Cardiac Arrest DHALADHULI JAHNAVI, ASHUTOSH DASH, MRINAL KUMAR ACHARYA, NIRMALYA GHOSH, AMIT PATRA Python N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE terablue_vikings N/A N/A N/A Priya Pattanaik, Upendra Kumar Jena, Python N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE The BEEGees 2380 35 Predicting Neurological Recovery from Coma After Cardiac Arrest from Multimodal EEG Data, using Audio-feature Transformation and Image-based Transfer Learning Felix Krones, Benjamin Walker, Guy Parsons, Adam Mahdi Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE The_Bee_Team N/A 448 Neurological Recovery Prediction from Coma after Cardiac Arrest Using Machine Learning Timothy S. Stamm, Prabhkirat S. Bindra, Syed Khairul Bashar N/A N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE The_Terrables N/A N/A N/A Rajlakshmi Borthakur, Mitesh Tank, Priya Ranjan Pattanaik, Upendra Jena Python N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TheBIGbrain N/A 434 Classifying EEG for Cardiac Arrest Recovery Outcome: Baseline Modeling with Feature Engineering-based Models Will Ke Wang, Leeor Hershkovich, Hayoung Jeong, Bill Chen, Jerry Yang, MD Mobashir Hasan Shandhi, Jessilyn Dunn Python P7_8 TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TsuiLab@CHOP 2600 271 Prediction of Neurological Outcome Using Clinical and Longitudinal EEG Data Combined in a Three-Way Ensemble Model Luiz Eduardo Silva, Victor M. Ruiz, Chao Chen, Tiffany Ko, Lingyun Shi, Fuchiang (Rich) Tsui Python N/A TRUE FALSE TRUE TRUE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE TUD_EEG 2557 15 Attention-based Multiple Instance Learning: towards Explainable Outcome Prediction in Comatose Patients after Cardiac Arrest Hongliu Yang, Ronald Tetzlaff Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE UCASFighters 2509 40 Predicting Neurological Recovery After Cardiac Arrest from Electroencephalogram with Multivariate Time-series Deep Neural Network Mengxue Yan, Beibei Wang Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE UFC_MDCC 2579 312 Exploring EEG Signal Features for Predicting Post Cardiac Arrest Prognosis Antonio Guilherme Cunha Santos, JOAO ALEXANDRE LOBO MARQUES, Luis Rigo Jr., Jo√£o Paulo Madeiro Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE UIU_MAU N/A 223 Prognosis of Cardiac Arrest Comatose using continuous EEG data Mohammad Aftab Uddin, Dewan Md. Farid Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE UniA4Life N/A 338 BrainFusion: An Ensemble Model for Neurological Outcome Prediction with Domain-Specific Features Benjamin Weigell, Fabian Stieler, Stefan Beil, Miriam Elia, Bernhard Bauer Python N/A TRUE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE unimi_bisp_squad 2217 238 Deep Learning-Based Prediction of Recovery from Coma After Cardiac Arrest using the Latest Five-Minute EEG Recording Available Filippo Uslenghi, Massimo W Rivolta, Roberto Sassi Python S62-5 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE Univ_Pittsburgh 2396 44 Predicting Recovery From Coma Following Cardiac Arrest With a Reduced Set of EEG Channels Nathan Riek, Jonathan Elmer, Salah Al-Zaiti, Murat Akcakaya Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE UOIML 2099 N/A N/A Konstantinos Blekas, Georgios Spithakis, Efstratios Miritzis, Python N/A FALSE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE UoM_EEE 2027 217 Autoencoder Artefact Removal for Brain Signals and Impact on Classification Performance Mengyao Li, Le Xing, Alexander J. Casson Python P7_8 TRUE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE TRUE UPFantastic N/A 324 EEG-Based Cardiac Arrest Outcome Estimation with Highly Interpretable Features Álvaro Bocanegra, Anaïs Espinoso, Ralph Gregor Andrzejak, Oscar Camara MATLAB R2022b P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE USYD_BrainBuzz 2370 311 A Multiresolution Data Augmentation in Transformer Architecture: Neurological Predictors from EEG for Comatose Recovery Simanto Saha, Andrea Samore, Andrew Goodwin, Collin Anderson, Michael Loong-Siong Wong, Raquib-ul Alam, Alistair McEwan MATLAB R2022b, MATLAB R2023a, Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE UTU_EEGenies 2228 341 Outcome Prediction of Comatose Patients after Cardiac Errest from EEG Using Random Forest and Expert Features Kianoosh Kazemi, Tuija Leinonen, Katri Karhinoja, Ismail Elnaggar, Sepehr Seifi Zarei, Matti Kaisti, Antti Airola Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE vee2team N/A N/A N/A Veena Gaonkar, Dr. T. Veerakumar, MATLAB R2022b N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE VitalLab 2581 306 Transfer Learning-based Machine Learning Model for Prediction of Neurological Recovery in Comatose Patients after Cardiac Arrest Hyeonhoon Lee, Gahee Choi, Soo Bin Yoon, Hyung-Chul Lee Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE WesternUni 2459 457 Predicting neurological recovery following cardiac arrest using EEG Matthew Kolisnyk, Xiaoyu Wang, Chao Guo, Karnig Kazazian, Loretta Norton, Saptharishi Lalgudi Ganesan, Adrian Owen, Derek Debicki Python N/A FALSE TRUE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE WomenLifeFreedom N/A 264 Predicting Neurological Recovery from Coma After Cardiac Arrest using Boosting Model with Time and Frequency Domain Features Zaniar Ardalan, Alex Lavaee, Saman Parvaneh Python N/A TRUE FALSE TRUE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE ZIB_Visual 2288 93 Predicting Coma Recovery After Cardiac Arrest With Residual Neural Networks Kuba Weimann, Tim O. F. Conrad Python P7_8 TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE TRUE ZJUT-Luckycloud 2203 145 Predicting Neurological Outcome from Electroencephalogram in Patients after Cardiac Arrest with Multi-Channel Transformer Jintao Zhu, Zhongli Huang, Luping Fang, Qing Pan Python P7_8 TRUE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE TRUE TRUE FALSE FALSE