Ranking (if eligible) on the test set Team Name Title Author(s) CinC Submission ID Accepted CinC abstract? Wild card CinC abstract? CinC preprint uploaded by deadline? Registered at CinC? Presented at CinC? Final CinC paper accepted by deadline? Withdrawn from CinC? Successful unofficial phase entry Successful official phase entry? Successfully trained on the training set and scored on the validation and test sets? Withdrawn from Challenge? Open-source license? Which license? Eligible for rankings and prizes? Final submission ID AUROC on the validation set AUROC on the test set AUPRC on the validation set AUPRC on the test set Accuracy on the validation set Accuracy on the test set F-measure on the validation set F-measure on the test set Reward on the validation set Reward on the test set Age-conditioned AUROC on the validation set Age-conditioned AUROC on the test set 1 NeuroUC3M SIREN: A Site-Invariant Rank Ensemble for Predicting Future Cognitive Impairment from Polysomnography María Muñoz Pérez, Alejandro Cañada Hinojosa, Lorena Gallego-Viñarás, Gonzalo Ricardo Ríos-Muñoz, Arrate Munoz-Barrutia 480 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2609 0.858 0.827 0.397 0.399 0.757 0.747 0.297 0.365 0.131 0.236 0.755 0.749 2 Matcha Hierarchical Multimodal Sleep Representation Learning for Cross-Site Cognitive Impairment Prediction Xinqi Bao, Saikat Chatterjee 79 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2692 0.805 0.773 0.280 0.305 0.816 0.588 0.299 0.271 0.122 0.129 0.737 0.727 3 CLECLINIC Deep Learning of Multimodal Features Derived from Raw Polysomnography for Cognitive Impairment Prediction Somesh Saini, Sikawat Thanaviratananich, Matheus Araujo 116 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2130 0.758 0.746 0.187 0.231 0.713 0.524 0.212 0.247 0.124 0.147 0.695 0.708 4 CAU_KU Late Fusion of Time-Domain and Time-Frequency Sleep EEG for Future Cognitive Impairment Prediction Nahyun Lee, TaeHwan Kim, TaeYoung Kang, DongJae Lee, DongGun Kim, Jeongbin You, Younghyuk Kim, Wuming Gong, Seungsang Oh, Il-Youp Kwak 71 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE MIT TRUE 2855 0.836 0.792 0.352 0.305 0.665 0.712 0.134 0.138 0.118 0.063 0.746 0.705 5 NeuroAI Cross-Site Stable Multiscale Sleep-Physiology Fusion for Predicting Future Cognitive Impairment Mohammad Hossein Behboudi, Nikkie Hooman 461 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2828 0.858 0.820 0.392 0.360 0.918 0.891 0.420 0.366 0.124 0.092 0.708 0.704 6 Better Call Sandman XGBoost versus Convolutional Neural Network Transfer Learning for Predicting Future Cognitive Impairment from Polysomnography Topi Niemi, Esko Toivonen, Mateusz Soliński, Venla Koivunen, Marjaana Nurmo, Noora Poutanen, Teemu Pukkila, Esa Rasanen 87 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2765 0.844 0.829 0.282 0.326 0.934 0.897 0.060 0.239 0.009 0.046 0.636 0.703 6 NLICA Fusion of Age-Residualized Engineered Sleep Features with Raw EEG for Predicting Future Cognitive Impairment Kab-Mun Cha, Joung Bae Choi, Hyo-Yeon Cho 593 TRUE TRUE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2361 0.835 0.787 0.302 0.314 0.895 0.871 0.359 0.344 0.172 0.159 0.736 0.703 8 Koalalition Age-Residualized Physiological Biomarkers and Gradient-Boosted Trees for Predicting Cognitive Impairment from Polysomnography Paul Fischer, Simon Boehi, Sidaty El Hadramy, Volodimir Buchakchiyskiy, Hélène Corbaz, Max Krähenmann, Philippe C. Cattin, Ece Ozkan 194 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2626 0.802 0.814 0.297 0.359 0.932 0.900 0.040 0.278 0.007 0.054 0.669 0.683 9 REMedy Multimodal PSG-Based Prediction of Cognitive Impairment Using an Interpretable XGBoost Framework Diego Cajal, Rodrigo Lozano Puñet, Josseline Madrid, Sofia Romagnoli 262 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2652 0.838 0.831 0.338 0.327 0.892 0.765 0.376 0.375 0.079 0.139 0.641 0.681 10 bashlab Cross-Site Generalization of Interpretable Sleep Features for Predicting Future Cognitive Impairment S. A. I. Shouborno, Bashima Islam 565 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2387 0.805 0.822 0.279 0.308 0.586 0.767 0.112 0.196 -0.215 0.104 0.528 0.678 11 Momochi-SleepAI Cognitive Impairment Prediction from Polysomnography Across Institutions: Contributions of Sleep Summaries and Sparse Electroencephalography Goeun Yeh, Muhi Kim, Jiyoung Park 175 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2075 0.649 0.727 0.119 0.222 0.909 0.768 0.178 0.297 0.062 0.187 0.601 0.673 12 Biosignal Pilots Predicting Cognitive Impairment From Polysomnography Using Combined Sleep Depth and Fragmentation Features Richard Hohmuth, Jakob J. Mueller, Hagen Malberg, Martin Schmidt 365 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE None (BSD-3 by default) TRUE 2771 0.760 0.797 0.320 0.320 0.065 0.113 0.122 0.178 -0.299 -0.158 0.636 0.671 12 MeDSP Integrating Sleep Macroarchitecture and Multi-Modal PSG Features for Cognitive Impairment Prediction Parisa Sattar, Marco Orrù, Maria Mura, Nicla Mandas, Eduardo Caballero Saldivar, iulia Baldazzi, Danilo Pani 216 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2262 0.755 0.730 0.173 0.266 0.648 0.502 0.216 0.239 0.120 0.110 0.708 0.671 14 BAPORLab Predicting Future Cognitive Impairment from Polysomnography with Stage-Aware Temporal Selection Hong-Cheol Yoon, Chang-Woo Kim, Hyun-Seok Kim, Woo-Young Seo, Sung-Hoon Kim 147 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2833 0.792 0.728 0.304 0.232 0.409 0.420 0.165 0.227 -0.138 -0.014 0.706 0.670 15 OCA-CENTINEL Capacity-Neutral Training Transfers Across Sites in Multimodal Sleep Prediction of Future Cognitive Impairment Junseob Kim, Aditya Nagori, Tilendra Choudhary, Md Hassanuzzaman, Rishikesan Kamaleswaran 390 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2632 0.735 0.687 0.257 0.217 0.856 0.628 0.265 0.245 0.072 0.098 0.658 0.666 16 OUS_IVS Cross-Site Prediction of Future Cognitive Impairment from Polysomnography Using Hybrid Physiological Representations Alireza Khorramfard, Naimahmed Nesaragi, Daniel Teichmann, Abdolrahman Peimankar 359 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2846 0.799 0.732 0.273 0.240 0.812 0.580 0.231 0.247 0.156 0.069 0.708 0.664 17 PhysioWinn Multi-Modal Representation Fusion with JEPA for Predicting Future Cognitive Decline Shyamal Y. Dharia, Stephen D. Smith, Camilo Valderrama 546 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2064 0.793 0.721 0.242 0.240 0.444 0.250 0.092 0.098 0.004 -0.123 0.748 0.658 18 Med_YNNU Dense Multi-Cale Time-Frequency Fusion Network with Hierarchical Attention for Screening Cognitive Impairment from Whole-Night Polysomnography Changsen Zi, Jingxiang Huang, Xuemin Yu, Yusi Zhu 177 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2630 0.722 0.701 0.137 0.233 0.716 0.654 0.217 0.261 0.037 0.030 0.646 0.636 19 UPV Maths Using a Frozen SleepFM Backbone to Predict Future Cognitive Impairment Through Polysomnography Jorge Reig-Aquino, Nuria Ortigosa 505 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2654 0.764 0.724 0.286 0.192 0.509 0.456 0.183 0.238 0.062 0.055 0.681 0.635 20 Revenger Cross-Site Generalization in PSG-Based Cognitive Impairment Screening and the Limits of Site-Proxy Evaluation Jingsu Kang, Hao Wen 196 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE MIT TRUE 2693 0.670 0.664 0.157 0.194 0.065 0.096 0.122 0.175 -0.299 -0.176 0.627 0.632 21 FuneLab Physiologically Informed Sensor Fusion for Cognitive Impairment Prediction from Polysomnography Joaquim Bauxell, Andriy Temko, Emanuel Popovici 274 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2237 0.782 0.670 0.278 0.231 0.899 0.830 0.296 0.306 0.253 0.142 0.729 0.630 22 Mind the Nap Heart Rate or Brain Waves? Sleep Signatures for Cognitive Impairment Detection Marion Taconné, Stefano Magni, Cristian Drudi, Filippo Emanuele Colella,, Anshum Patel, Joseph Cheung, Valentina DA Corino, Anna Maria Maddalena Bianchi, Pietro Cerveri, Riccardo Barbieri, Luca Mainardi 321 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2495 0.593 0.668 0.103 0.153 0.530 0.505 0.150 0.234 -0.027 0.069 0.600 0.629 23 Kust_MeAI Transfer Learning from a Multimodal Sleep Foundation Model for Cognitive Impairment Prediction Using Polysomnography and Clinical Features Jingming Zhang, Zijie Zhu, Chaoyu Wei, Zhibin Deng, Ziqin Yuan, Xue Luo, Lei Yang, Ziling Lan, Yuqi Wang, Pan Xia 218 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE Creative Commons Attribution-NonCommercial 4.0 TRUE 2831 0.735 0.727 0.227 0.226 0.935 0.904 0.000 0.000 0.008 0.007 0.655 0.626 24 OOM_finder Predicting Future Cognitive Impairment Using Whole-Night Sleep-Derived Outcomes Franz Ehrlich, Sara Bäcker, Alex Schmidt, Nicolai Spicher, Dagmar Krefting, Miriam Goldammer, Philip Hempel 384 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2715 0.740 0.802 0.332 0.309 0.906 0.570 0.396 0.279 0.157 0.013 0.703 0.624 25 ISIBrno-AIMT The Age is a Strong Baseline: But Is There Anything Beyond? Petr Nejedly, Pavel Jurak, Filip Plesinger 203 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2410 0.770 0.760 0.257 0.224 0.911 0.881 0.259 0.188 0.034 0.010 0.554 0.623 26 Arnav & Ivan Stable4: Four Pretrained Sleep-EEG Outputs for Future Cognitive Impairment Arnav Mana, Ivan Habib 581 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2593 0.738 0.749 0.318 0.308 0.332 0.560 0.155 0.260 -0.033 0.087 0.723 0.622 27 BetterPSG Integrating Sleep Foundation Model Representations and Digital Biomarkers for Age-Aware Cognitive Risk Prediction Leyu Zhou, Donglin Xie, Guangkun Nie, Jinshuai Gu, Qingshuo Zhao, Shijie Chen, Deyun Zhang, Yuxi Zhou, Shenda Hong 113 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2505 0.799 0.779 0.226 0.264 0.089 0.162 0.123 0.185 -0.302 -0.125 0.626 0.620 28 Lotus Sleep Analysts Rank Inversion in PSG Model Selection under Leave-One-Site-Out Evaluation Hongi Nagaputra, Weije Sheng, Yuantao Qi, Zhijun Xiao, Yunyi Jiang, Caiyun Ma 48 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2353 0.727 0.692 0.163 0.205 0.935 0.904 0.000 0.000 0.008 0.007 0.647 0.614 29 gdub Age-Conditioned Evaluation of Handcrafted Polysomnography Models for Cognitive-Impairment Prediction Satwik Kapavarapu, Nathan Hoang, Andrei Malagusan 566 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2163 0.746 0.768 0.201 0.247 0.424 0.302 0.077 0.144 -0.186 -0.083 0.486 0.610 30 Sleepyhead Predicting Cognitive Impairment from Polysomnography using a multi-site Light Gradient-Boosting Machine Approach Mario Tapia-Pacheco, Aneequa Sundus, Achal Dhupa, Vinay Pai 59 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2634 0.857 0.792 0.394 0.273 0.923 0.711 0.409 0.325 0.168 0.078 0.748 0.606 31 SECVC Autonomous Agentic Experimentation for Predicting Cognitive Impairment from Polysomnography Gyula Bohus, József Nagy-Bozsoky, Klaudia Vivien Nagy 454 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2813 0.798 0.751 0.262 0.254 0.774 0.459 0.203 0.208 0.166 -0.026 0.672 0.604 32 REMember Us Annotation-Derived Sleep Features Outperform End-to-End Raw PSG Modeling for Cognitive-Impairment Prediction Bjørn-Jostein Singstad, Helene Brodin, Kjersti Grande 126 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2792 0.689 0.738 0.180 0.249 0.742 0.763 0.197 0.311 -0.013 0.091 0.512 0.601 33 SleeperAgents Predicting Cognitive Impairment from Polysomnography with Tabular Foundation Model and Markov Transition Matrix Kelvin K Nguyen, Arshia Ilaty, Andy Smithwick, Arash Shokouhmand, Kingson Zhang, Elahe Khatibi, Sogol Sanjaripour, Jungsoo Lee, Shadi Manafi, Shahab Nikkhoo, Zaniar Ardalan, Saman Parvaneh 98 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2758 0.769 0.750 0.199 0.211 0.935 0.904 0.000 0.000 0.008 0.007 0.605 0.595 34 Everybody Hearts (REM) Annotation-Guided Temporal Attention with a Sleep Foundation Model for Predicting Future Cognitive Impairment from Polysomnography Xiaoyu Wang, Weiping Liu, Yixuan Zhang, Jiawei Wu, Bin Chi, Yiran Fu, Xiaojun Ning, Jing Wang, David C. Wong 178 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2687 0.853 0.784 0.372 0.226 0.679 0.284 0.262 0.207 0.139 -0.089 0.705 0.594 35 Blue and Gold Frozen SleepFM and engineered polysomnographic features for prediction of subsequent cognitive impairment diagnoses Karen K. Wurzel, David J. Kaftan, Matthew Joseph Dupont, Richard J. Povinelli 553 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2801 0.748 0.671 0.289 0.193 0.468 0.237 0.167 0.189 0.016 -0.084 0.698 0.593 36 SwatBeat Robust Feature Discovery for the Prediction of Incident Dementia from Multi-Source Sleep Studies Allan R. Moser, Sai Nyi Bhone Htut 245 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2347 0.867 0.806 0.376 0.295 0.814 0.676 0.343 0.325 0.062 0.042 0.729 0.587 37 MeDiTechDreamers Leveraging large-scale pretrained sleep models via multi-modal fusion for early prediction of cognitive impairment Alvise Dei Rossi, Alessia Calzoni, Giuliana Monachino, Beatrice Zanchi, Luigi Fiorillo 330 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2714 0.740 0.679 0.244 0.188 0.883 0.552 0.352 0.233 0.242 0.017 0.702 0.565 38 CardioAI Screening for Cognitive Impairment from Sleep Architecture: Dual-Head Age-Conditioned Ranking and Prevalence-Weighted Decisions Rishabh Jha, Amrita Singh, Kumar Prasun, Anju Gandhi Bhandari 476 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2678 0.700 0.591 0.211 0.163 0.380 0.459 0.043 0.056 -0.186 -0.126 0.597 0.534 39 GT NeuroSignals Lab Site Aware Stacking for Cross Center Cognitive Risk Modeling From Overnight Polysomnography Yuxuan Xu 31 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2029 0.618 0.620 0.183 0.155 0.066 0.102 0.122 0.176 -0.297 -0.169 0.515 0.521 40 Leicester Fox Multimodal Late-Fusion Prediction of Cognitive Impairment from Polysomnography Using Metadata and Timing-Aware Signal Features Xin Li, Ekenedirichukwu N. Obianom, Abdulhamed M. Jasim,, Shamsu Idris Abdullahi, Fan Feng, Abdulmalik, Koya,, G André Ng, Noor N. Qaqos 325 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2718 0.457 0.511 0.060 0.102 0.641 0.816 0.093 0.032 -0.151 -0.080 0.473 0.509 41 QueensOfDreams_UMG Predicting Cognitive Impairment from Polysomnography using Graph Neural Networks Friederike Seyderhelm, Gesa Klukaschewski, Tabea Steinbrinker, Kristin Elisabeth Steinhaus, Anne-Christin Hauschild, Miriam Cindy Maurer 368 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2566 0.538 0.549 0.074 0.118 0.861 0.848 0.092 0.124 -0.032 0.005 0.530 0.503 42 OneHeart OneHeart: Predicting Cognitive Impairment using Heart Rate Variability and Demographics Edo Ikurumi, Katsuhito Fujiu 408 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 TRUE 2832 0.488 0.456 0.085 0.091 0.065 0.096 0.122 0.175 -0.299 -0.176 0.589 0.449 N/A 1201usst N/A LvZongYu, LiRuiWen N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A Adrian Williams Clinical Machine Learning Can Perform Well by Learning the Dataset Rather Than the Patient Darnell K. Adrian Williams II 594 TRUE TRUE TRUE TRUE FALSE FALSE FALSE TRUE TRUE FALSE TRUE None (BSD-3 by default) FALSE 2301 0.667 0.724 0.140 0.184 0.525 0.706 0.168 0.292 -0.095 0.031 0.556 0.605 N/A AIMED Multimodal Sleep Signal Modeling with Multi-Task Learning and Transformers for Cognitive Impairment Detection Quenaz Bezerra Soares, Estela Ribeiro, Felipe Meneguitti Dias, Diego A. Cardona Cardenas, Joseph Pena, Marcelo Toledo, Jose Krieger, Marco Antonio Gutierrez 484 TRUE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2739 0.585 0.592 0.090 0.117 0.879 0.811 0.095 0.115 -0.006 -0.022 0.579 0.594 N/A AIMS-Lab Multimodal Sleep Feature Extraction and Stratified Feature Selection for Dementia Prediction Bálint Kristóf, Szabolcs M. Péter, Kristóf Müller, Márton A. God 193 TRUE FALSE TRUE TRUE TRUE FALSE TRUE TRUE TRUE TRUE TRUE BSD-3 FALSE 2863 0.884 0.807 0.396 0.282 0.936 0.904 0.022 0.000 0.011 0.007 0.727 0.608 N/A AP Lab N/A Dominik Ludera, Marta Kersten-Oertel N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2346 0.784 0.810 0.284 0.355 0.651 0.663 0.159 0.247 0.040 0.152 0.674 0.709 N/A apple_dream Sleep Architecture Signatures for Cognitive Impairment Detection via Site-Normalized Penalized Logistic Regression Hector Uriel Chavez Loyola 270 TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A bci team Predicting Future Cognitive Impairment Risk from Multimodal Polysomnography and Automated Sleep Annotations Hao Jie Gao, Lili Du, Rui Yu, Lina Chen, Zhu Mingyu, Sizhang Duan, binghong Cai, Guangyu Bin 84 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE N/A FALSE N/A N/A BCVSP N/A Fouzul Hassan, Yenuli Sooriyaarachchi, Indrajith Ekanayake, Dr. Thanuja D. Ambegoda, Akarshani Ramanayaka, Sankeetha Elancheliyan, Tharushi Pramoda Amarabandu, Dilanka Perera, Janeesha Kankanamga N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2310 0.710 0.705 0.156 0.193 0.693 0.555 0.124 0.154 0.047 -0.117 0.580 0.545 N/A BioAI-UDFJC N/A Jonathan Roberto Torres Castillo, Julián Leonardo González Espejo, Ian Nicolás Sandoval Martínez, Sergio Nicolás Osorio Guevara, Yeremy Vega Pineda, Andrés Felipe Muzu Yupangui, Sebastián David Trujillo Vargas, Yhoan Mauricio Bermúdez Tique N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2533 0.835 0.816 0.275 0.303 0.932 0.900 0.171 0.155 0.013 0.015 0.587 0.639 N/A BIOWAVE Lab N/A Melanie Valiente Puche, Erick González Marrugo , Daniel Martinez Vivero, Maria Camila García Salazar N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A Boussina-Lab Tabular Feature-Based Prediction of Cognitive Impairment from Polysomnography Using LightGBM Hetvi Majmudar, Sai Shruthik Volety 540 TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A Buck_AI N/A Francisco José de Caldas N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2790 0.491 0.262 0.075 0.080 0.591 0.440 0.043 0.042 0.007 -0.124 0.627 0.523 N/A CapyBraina N/A Benjamin Pike N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2748 0.768 0.775 0.151 0.255 0.890 0.868 0.124 0.312 0.018 0.117 0.638 0.622 N/A CardioID Multimodal Learning for Cognitive Impairment Prediction in Sleep Studies Aristotelis Styanidis, Andre Ribeiro Lourenco, Carlos Carreiras, George Yannis 322 FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A CasaNight A Multimodal Approach for Cognitive Impairment Prediction Using Physiological Signals and Recurrent Neural Networks Rabie Fadil 443 FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A CCA_BH Polysomnographic Waveforms and Derived Sleep Metrics as Complementary Encoders of Preclinical Cognitive Impairment Corneliu C. Antonescu 72 TRUE FALSE TRUE TRUE FALSE TRUE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2780 0.869 0.815 0.398 0.335 0.770 0.550 0.331 0.278 0.223 0.124 0.741 0.715 N/A CeZIS N/A Unknown N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE GPL-3 FALSE N/A N/A CLJ Ulm N/A Luca Rohmann, Jan Baisch, Christoph Roß, Walter Karlen, Tugce Canbaz N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2106 0.845 0.815 0.364 0.325 0.902 0.444 0.263 0.188 0.207 -0.070 0.709 0.615 N/A CMCR UJ CM Multi-Modal Sleep Analysis for Cognitive Impairment Detection Michał Szafarczyk, Szymon Gaczoł, and Tomasz Więcek 413 TRUE FALSE TRUE TRUE TRUE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A CodingNeuro Learning Latent Sleep Dynamics from Multimodal Polysomnography for Mild Cognitive Impairment Prediction: A Fractal Analysis-Based Method Sheng Yan Sun 211 TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A CognitionOMNIA N/A Sahen Tapar N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2088 0.635 0.547 0.109 0.112 0.935 0.904 0.000 0.000 0.008 0.007 0.665 0.589 N/A CorazonConsado Hybrid Convolutional Transformer and Long Short-Term Memory Deep Learning Model for Predicting Cognitive Decline Using Polysomnography Zoe E. Boysen, Isabel McIntyre, Emilia V Fallman, Emma C Boysen 575 TRUE FALSE TRUE TRUE TRUE FALSE FALSE FALSE FALSE FALSE FALSE N/A FALSE N/A N/A Dachshund Legacy A Multimodal Residual Spectrogram Encoder with Disentangled Private and Shared Embeddings for Predicting Cognitive Impairment from Polysomnography. Fredric Engblom 394 TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A DeepHypnos DeepHypnos: Predicting Future Cognitive Impairment from Polysomnography Using Attention-Pooled Sleep Foundation Model Embeddings Aristotelis Ballas, Vasileios Papapanagiotou, Christos Diou 85 TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE None (BSD-3 by default) FALSE N/A N/A DKAW the Lone Survivor N/A Darnell K Adrian Williams N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE None (BSD-3 by default) FALSE 2442 0.500 0.500 0.065 0.096 0.935 0.904 0.000 0.000 0.008 0.007 0.500 0.500 N/A DLAB N/A Yeongdon Kim N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A DSAIL-Alpha N/A Victor Ruto, Paul Bett, David Warutumo, Clinton Mwangi, David Warutumo N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A Ex juvantibus N/A Basheer Marzoog, Anastasiia Stroeva N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2300 0.849 0.814 0.285 0.281 0.905 0.835 0.335 0.383 0.024 0.049 0.619 0.630 N/A ForFun N/A Unknown N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2183 0.682 0.727 0.218 0.224 0.904 0.756 0.267 0.305 0.079 0.092 0.603 0.663 N/A GoldenEagleAI HARMONIC++: Heterogeneity-Aware Robust Multimodal Optimization for Cross-Site Cognitive Impairment Prediction from Polysomnography Iftakhar Ali Khandokar, Priya Deshpande 564 TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE N/A FALSE N/A N/A Hanumu N/A Bhargav Kowshik N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A Headington Dreamers Predicting Cognitive Impairment using Gated Attention Pooling of Sleep Epoch Features Jonathan F. Carter, Shaun Davidson, Cristian Roman, Lionel Tarassenko 58 TRUE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE TRUE MIT FALSE 2394 0.836 0.767 0.316 0.231 0.936 0.872 0.345 0.244 0.096 0.036 0.732 0.693 N/A HEAT_ETRI Robust Cross-Site Prediction of Cognitive Impairment from Polysomnography through Sleep Feature Selection and Ensemble Learning Se Won Oh, Hyuntae Jeong, Seungeun Chung, Sunkyung Lee, Jeong Mook Lim, Kyoung Ju Noh 33 TRUE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2514 0.636 0.774 0.143 0.297 0.425 0.713 0.103 0.260 -0.154 0.132 0.545 0.669 N/A HJKL-IoMT-2026 N/A Junhao Zhang, Luotong Li N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2110 0.765 0.757 0.254 0.237 0.591 0.443 0.196 0.240 -0.113 0.059 0.566 0.577 N/A HKUSTGZ - ML4H Whole-Night Temporal Modeling and Multimodal Fusion for Cognitive Impairment Prediction from Heterogeneous Polysomnography Muchen Li 353 TRUE FALSE FALSE FALSE FALSE TRUE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2194 0.637 0.653 0.097 0.182 0.726 0.701 0.177 0.241 -0.057 0.096 0.580 0.583 N/A HutkaCode N/A Peter Huťka, PhD., MUDr. Sára Kušnierová N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2377 0.786 0.627 0.217 0.181 0.889 0.781 0.275 0.251 0.090 0.092 0.716 0.586 N/A Inception vKISMED Predicting Cognitive Impairment from Polysomnograms with Block-Recurrent Transformers Jad Haidamous, Christoph Hoog Antink 105 TRUE FALSE FALSE TRUE FALSE TRUE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A Insomniac111 Prediction of Cognitive Impairment from Polysomnography Using XGBoost and a Pretrained Tabular Foundation Model (TabPFN V2) Elaine Li 18 TRUE FALSE TRUE TRUE FALSE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2698 0.851 0.748 0.397 0.238 0.913 0.774 0.410 0.293 0.263 0.113 0.765 0.604 N/A JSPS São Luís MA Brasil Predicting Future Cognitive Impairment Using Polysomnography Signals and Demographic Features Jhôwfrann dos Santos Pinheiro Silva, Stefany Medeiros Castello Branco 32 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE N/A FALSE N/A N/A KBA Are Complex Models Always Better? Cross-Site Generalization in Cognitive Impairment Prediction from Sleep Studies Heidar Mar Thrainnsson, Zhongxing Zhang, Ramin Khatami 514 TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A labnofer N/A Navid Malekan, Arefeh Pasdar, Erfan Mokhberian N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2083 0.783 0.751 0.208 0.279 0.925 0.881 0.117 0.345 0.007 0.081 0.630 0.583 N/A LEB USP N/A João Vitor de Amorim, Renata Valeri de Freitas, Gustavo Bergamo , Rodrigo Alonso, João Nonato, Beatriz Tapia N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A LisbonSleep N/A Flávio Ferreira N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A Magic N/A 杜丽莉, 段思彰, 段思彰, 杜丽莉, 杜丽莉, 杜丽莉, 余睿, 陈丽娜, 朱明玉, 段思彰, 蔡秉宏, 宾光宇 N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2299 0.558 0.640 0.112 0.162 0.517 0.329 0.138 0.196 -0.019 -0.058 0.587 0.624 N/A Medics Tensor-Based Analysis for Cognitive Impairment Prediction Using Polysomnography Signals Zindia Kapil Raikar, Shivnarayan Patidar 336 FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2685 0.708 0.702 0.154 0.207 0.621 0.695 0.197 0.276 0.085 0.010 0.599 0.529 N/A MiCOR-PSG Learning Multiscale Polysomnography Representations with Hierarchical Transformers for Predicting Future Cognitive Impairment Paolo G. Cachi, Soroosh Solhjoo 70 TRUE FALSE TRUE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE MIT FALSE 2885 0.563 0.763 0.083 0.302 0.193 0.806 0.130 0.349 -0.280 0.027 0.422 0.501 N/A Mousa Shaya N/A Mousa Shaya N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2096 0.607 0.600 0.099 0.160 0.354 0.351 0.153 0.199 -0.137 -0.176 0.467 0.473 N/A Multimodal_Owls N/A Antonio Mendoza N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A NETMIT Leveraging Physiological Embeddings for Cognitive Impairment Detection in Multimodal Sleep Studies Sophia Zhang, Ali Mirzazadeh 108 TRUE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2441 0.835 0.815 0.325 0.340 0.935 0.905 0.042 0.031 0.010 0.011 0.723 0.745 N/A Neurion Cross-Site Evaluation of Demographic and Sleep-Annotation Features from Polysomnography for Cognitive Impairment Prediction Aans Noufal, Emadaddin Al-Qadasi, Florian Finn Keuren, Marc Volpe-Prignano Garcia, Mykhailo Bratskov 364 TRUE FALSE FALSE FALSE FALSE TRUE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A NeuroNoctis N/A Yuxuan Xu N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A Neurosys26 N/A Unknown N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2137 0.456 0.718 0.086 0.191 0.935 0.898 0.021 0.015 0.009 -0.001 0.550 0.491 N/A No known team name Predicting Cognitive Impairment from Polysomnography Using Hybrid Hand-Crafted and Deep Learning Features with Gradient Boosting Efrain Manuel Magana, Juan Ignacio Ortega Flores 357 TRUE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE FALSE FALSE N/A FALSE N/A N/A No known team name Multimodal and Interpretable Prediction of Future Cognitive Decline from Clinical Polysomnography Santiago Ismael Flores-Chavez, Marjoriet L. Peñaloza Zurita, Carlos Eduardo Salazar Coaguila, Antonio Gabriel Ravelo-Garcı́a, Victor Andres Cabrera-Caso, Miguel Vizcardo 578 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE N/A FALSE N/A N/A no_sleep Predicting Cognitive Impairment from Polysomnography: Integration of Demographic Factors and Latent Sleep Embeddings Chito Patiño, Zoher Orabe, Ajdar Ullah, Jonas Julius Sandelin, Matti Kaisti, Antti Airola 524 TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A NUS Sleepy Scientists N/A Siyu Zhang, Ruowang Dong N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2858 0.772 0.785 0.242 0.302 0.934 0.887 0.041 0.323 0.011 0.074 0.631 0.654 N/A OSF N/A Zitao Shuai, Zongzhe Xu, Yuzhe Yang N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2561 0.826 0.796 0.308 0.389 0.513 0.531 0.193 0.257 -0.094 0.082 0.651 0.669 N/A OucruForFun N/A Van-Khoa D. Le N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2425 0.745 0.743 0.278 0.257 0.900 0.702 0.311 0.294 0.086 0.131 0.672 0.673 N/A PES Signal Syndicate N/A V Saatwik, Sumukh Shandilya, Varshit Gude, Ritu Ravish N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2636 0.629 0.534 0.107 0.109 0.713 0.483 0.167 0.176 -0.010 -0.050 0.597 0.522 N/A POLSL N/A Filip Skwarek, Kacper Wydra, Dawid Patucha, Mateusz Hajda, Eryk Dyrek, Krzysztof Fajfer N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2079 0.855 0.778 0.321 0.305 0.261 0.485 0.113 0.176 -0.238 -0.078 0.666 0.593 N/A Pulse Saver N/A Aarav Kaashyap N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2591 0.871 0.769 0.404 0.270 0.935 0.905 0.021 0.127 0.010 0.022 0.700 0.546 N/A ReCognition N/A Anirban Dutta Choudhury, Ayan Mukherjee, Shilajit Banerjee, Chandan Pandey, Shreyasi Datta, Meghna Pandharipande, Tanuka Bhattacharjee, Gauri Deshpande, Aniruddha Sinha N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2486 0.822 0.682 0.299 0.196 0.864 0.770 0.371 0.257 0.322 0.027 0.795 0.639 N/A REM and Reason End-to-End Fine-Tuning of Modality-Specific PSG Foundation Models for Cognitive Impairment Prediction Maximilian Riehl, Veronika Koch, Svenja Klamt, Laurenz Ottmann, Maximilian Paul Oppelt 529 TRUE FALSE FALSE TRUE TRUE TRUE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2571 0.632 0.588 0.107 0.113 0.853 0.838 0.154 0.070 -0.010 -0.032 0.519 0.511 N/A SHANK Minimal Site-Robust Sleep Features for Predicting Cognitive Impairment from Polysomnography Shankar Biswas, Sindhu Vasireddy, Yashasvi Srivastava, Raja Kollu, Vivek Yedavalli 378 TRUE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A Sleep_sue N/A Esperanza Camargo N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2560 0.672 0.693 0.198 0.190 0.932 0.773 0.185 0.275 0.038 0.119 0.580 0.632 N/A SleeperAgentZzz Predicting Cognitive Impairment from Sleep Structure with Hierarchical Sleep Foundation Model Tokens Florian Herzler, Maximilian Otto 463 TRUE FALSE TRUE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2882 0.598 0.664 0.139 0.168 0.767 0.532 0.179 0.231 0.036 0.071 0.605 0.660 N/A SleepLens What the Sleeping Heart Reveals About Future Cognitive Decline Darya Yelshyna 534 TRUE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2768 0.798 0.764 0.343 0.280 0.939 0.868 0.326 0.342 0.053 0.106 0.611 0.569 N/A SleepSentinels Multimodal Polysomnography Representation Learning for Cognitive Impairment Screening Alex Fedorov, Tian Xia, Nutan Sahoo, Anamika Kumari, Sulaiman Vesal 277 TRUE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2308 0.644 0.644 0.192 0.171 0.233 0.384 0.034 0.047 -0.331 -0.150 0.555 0.541 N/A SomnoCognition N/A Unknown N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2073 0.663 0.708 0.119 0.203 0.765 0.688 0.173 0.261 -0.007 -0.032 0.560 0.538 N/A SomnoSense Multimodal Sleep Signal Phenotyping for Predicting Future Cognitive Impairment Sejuti Dhali, Tasmeya Siddique Mayesha 462 TRUE FALSE TRUE TRUE TRUE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A SomnoTrace Predicting future cognitive impairment from overnight PSG recordings using feature engineering and deep sequence models Pinar Bisgin, Harshini Eggoni, Martin Sondermann, Rene Brinkhege, Brian-Frederik Jahnke 123 TRUE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE N/A FALSE N/A N/A Spectra N/A Unknown N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A Stratified AI Predicting cognitive impairment from polysomnography using multimodal handcrafted features and gradient boosting Muhammad Moeez, Hiba Mazhar 291 FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A SynthAI Sleep2Cognition: Efficient Hybrid Multimodal Learning for Cognitive Risk Prediction from Polysomnography Ruhallah Amandi 499 FALSE FALSE FALSE FALSE FALSE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A sysneuron26 N/A Perraju Tolety N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE MIT FALSE 2003 0.738 0.668 0.212 0.154 0.935 0.903 0.000 0.000 0.008 0.005 0.585 0.486 N/A Team Narnia N/A Brian Dillon N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2156 0.826 0.811 0.303 0.320 0.869 0.652 0.372 0.316 0.101 0.069 0.660 0.600 N/A TemporalSync Multimodal Learning from Polysomnography for Early Detection of Cognitive Impairment Florian Luebbe 266 TRUE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2212 0.712 0.785 0.194 0.294 0.935 0.905 0.000 0.075 0.008 0.015 0.560 0.633 N/A ThoroughbredHerd Predicting Cognitive Impairment from Polysomnography Using Multimodal Foundation Models and Spatiotemporal Networks Sudhir K. Koneru 559 TRUE FALSE FALSE TRUE TRUE FALSE TRUE FALSE FALSE FALSE TRUE BSD-3 FALSE N/A N/A TLAN_ULM N/A Unknown N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2211 0.828 0.795 0.279 0.309 0.613 0.334 0.232 0.216 -0.020 -0.131 0.644 0.611 N/A UCAS_HypothesisZone Channel-Adaptive Multiview Polysomnography for Early Risk Estimation of Cognitive Impairment ChaoYi Zhu, Caibao Huang, Lanqi Yu 163 FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE N/A FALSE N/A N/A unchartered iitian N/A Priyansh Gadia N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2428 0.721 0.767 0.217 0.252 0.703 0.570 0.221 0.278 0.009 0.033 0.553 0.597 N/A Undae N/A Arnaud Poletto N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2005 0.757 0.716 0.190 0.215 0.731 0.662 0.236 0.276 0.080 0.154 0.649 0.613 N/A Worse_Than_CC N/A Jiayuan Pham N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2057 0.552 0.617 0.108 0.130 0.294 0.689 0.128 0.194 -0.208 -0.018 0.478 0.568 N/A yash_onward_IITR N/A Yash Bansal N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2764 0.822 0.833 0.301 0.341 0.931 0.871 0.290 0.390 0.053 0.072 0.674 0.686 N/A YoYo N/A Chuanqi Zou N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2521 0.634 0.707 0.124 0.194 0.804 0.518 0.191 0.238 0.066 0.117 0.609 0.669 N/A ZHXTeam N/A Unknown N/A FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE TRUE TRUE FALSE TRUE BSD-3 FALSE 2169 0.500 0.500 0.065 0.096 0.935 0.904 0.000 0.000 0.008 0.007 0.500 0.500 N/A Zzzzürich Polysomnography-based Sleep Representations via Latent Attention Masked Autoencoders for Cognitive Impairment Prediction Luigi Pizza, Moritz Vandenhirtz, Samuel Ruiperez-Campillo, Thomas M. Sutter, Julia E. Vogt 197 TRUE FALSE FALSE FALSE FALSE TRUE TRUE TRUE TRUE FALSE TRUE BSD-3 FALSE 2341 0.597 0.681 0.114 0.161 0.902 0.832 0.136 0.209 -0.001 0.022 0.444 0.581