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Sleep Stage Detection

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하위 태스크: 1
평가표: 16
보존된 평가 기록: 55

Human Sleep Staging into W-N1-N2-N3-REM classes from multiple or single polysomnography signals

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/Dreem-Organization/RobustSleepNet

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RobustSleepNet: Transfer learning for automated sleep staging at scale

https://github.com/Dreem-Organization/dreem-learning-evaluation

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Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep staging

https://github.com/Dreem-Organization/dreem-learning-open

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Dreem Open Datasets: Multi-Scored Sleep Datasets to compare Human and Automated sleep staging

https://github.com/HuayuLiArizona/Conformalized-Multiple-Instance-Learning-For-MedTS

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Enhancing Visual Inspection Capability of Multi-Modal Large Language Models on Medical Time Series with Supportive Conformalized and Interpretable Small Specialized Models

https://github.com/IoBT-VISTEC/MetaSleepLearner

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MetaSleepLearner: A Pilot Study on Fast Adaptation of Bio-signals-Based Sleep Stage Classifier to New Individual Subject Using Meta-Learning

https://github.com/Jeongseungwoo/Efficient-Continuous-Manifold-Learning

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Deep Efficient Continuous Manifold Learning for Time Series Modeling

https://github.com/Mithunjha/EarEEG_KnowledgeDistillation

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A Knowledge Distillation Framework For Enhancing Ear-EEG Based Sleep Staging With Scalp-EEG Data

https://github.com/Niloy333/eegFloss

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eegFloss: A Python package for refining sleep EEG recordings using machine learning models

https://github.com/Raminghorbanii/Self-Supervised-PPG-Representation-Learning-Shows-High-Inter-Subject-Variability

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Self-Supervised PPG Representation Learning Shows High Inter-Subject Variability

https://github.com/SajadMo/SleepEEGNet

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SleepEEGNet: Automated Sleep Stage Scoring with Sequence to Sequence Deep Learning Approach

https://github.com/TDA-Jyamiti/zzgril

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Quasi Zigzag Persistence: A Topological Framework for Analyzing Time-Varying Data

https://github.com/acrophase/sleep_staging_kd

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A Deep Knowledge Distillation framework for EEG assisted enhancement of single-lead ECG based sleep staging

https://github.com/ai4healthuol/s4sleep

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S4Sleep: Elucidating the design space of deep-learning-based sleep stage classification models

https://github.com/akaraspt/deepsleepnet

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DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

https://github.com/biomedical-signal-processing/sleepyland

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SLEEPYLAND: trust begins with fair evaluation of automatic sleep staging models

https://github.com/dlcjfgmlnasa/NeuroNet

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NeuroNet: A Novel Hybrid Self-Supervised Learning Framework for Sleep Stage Classification Using Single-Channel EEG

https://github.com/dlcjfgmlnasa/SynthSleepNet

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Toward Foundational Model for Sleep Analysis Using a Multimodal Hybrid Self-Supervised Learning Framework

https://github.com/dslaborg/frequency-pretraining

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Data-Efficient Sleep Staging with Synthetic Time Series Pretraining

https://github.com/dslaborg/sumov2

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From Sleep Staging to Spindle Detection: Evaluating End-to-End Automated Sleep Analysis

https://github.com/ecgresearch/heartbert

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HeartBERT: A Self-Supervised ECG Embedding Model for Efficient and Effective Medical Signal Analysis

https://github.com/emadeldeen24/ADAST

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ADAST: Attentive Cross-domain EEG-based Sleep Staging Framework with Iterative Self-Training

https://github.com/gist-ailab/IITNet-official

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Intra- and Inter-epoch Temporal Context Network (IITNet) Using Sub-epoch Features for Automatic Sleep Scoring on Raw Single-channel EEG

https://github.com/gist-ailab/sleepyco

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SleePyCo: Automatic Sleep Scoring with Feature Pyramid and Contrastive Learning

https://github.com/hsd1503/DL-ECG-Review

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Opportunities and Challenges of Deep Learning Methods for Electrocardiogram Data: A Systematic Review

https://github.com/jathurshan0330/cross-modal-transformer

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Toward Interpretable Sleep Stage Classification Using Cross-Modal Transformers

https://github.com/jukiecheung/mvitime

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Contrastive Learning for Sleep Staging based on Inter Subject Correlation

https://github.com/komdec/detectsleepnet

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An Interpretable and Efficient Sleep Staging Algorithm: DetectsleepNet

https://github.com/ku-milab/transsleep

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TransSleep: Transitioning-aware Attention-based Deep Neural Network for Sleep Staging

https://github.com/likith012/muleeg

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mulEEG: A Multi-View Representation Learning on EEG Signals

https://github.com/mHealthBuet/ASSC

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End-to-end Sleep Staging with Raw Single Channel EEG using Deep Residual ConvNets

https://github.com/majy-yuji/st-usleepnet

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ST-USleepNet: A Spatial-Temporal Coupling Prominence Network for Multi-Channel Sleep Staging

https://github.com/mathieuseraphim/spdtransnet

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Structure-Preserving Transformers for Sequences of SPD Matrices

https://github.com/navsnav/RBD-Sleep-Detection

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Detection of REM Sleep Behaviour Disorder by Automated Polysomnography Analysis

https://github.com/pquochuy/MultitaskSleepNet

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Joint Classification and Prediction CNN Framework for Automatic Sleep Stage Classification

https://github.com/pquochuy/SeqSleepNet

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SeqSleepNet: End-to-End Hierarchical Recurrent Neural Network for Sequence-to-Sequence Automatic Sleep Staging

https://github.com/pquochuy/l-seqsleepnet

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L-SeqSleepNet: Whole-cycle Long Sequence Modelling for Automatic Sleep Staging

출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.