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Paper Citation Record · LEDGER

Multi-task deep-learning for sleep event detection and stage classification

As of 11 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2501.09519.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.09519 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T19:59:06.794888Z

measured 36 of 36 standing notices

One-hop event checks from named stored sources.

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

36 of 36 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f872d4f2-d02c-4793-9c81-17e024b4f850 · outbound

This paper cites Short-and long-term health consequences of sleep disruption,.

Multi-task deep-learning for sleep event detection and stage classification Short-and long-term health consequences of sleep disruption,

Reference 1

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Observation cfe39be0-ab84-4c68-8ac2-9013b38150bc · outbound

This paper cites Sleep deprivation and its association with diseases-a review,.

Multi-task deep-learning for sleep event detection and stage classification Sleep deprivation and its association with diseases-a review,

Reference 2

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Observation 2e73efa0-8e97-41d0-a10a-442a0c6fde73 · outbound

This paper cites The aasm manual for the scoring of sleep and associated events: rules, terminology and technical specifications (version 3),.

Multi-task deep-learning for sleep event detection and stage classification The aasm manual for the scoring of sleep and associated events: rules, terminology and technical specifications (version 3),

Reference 3

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Observation 2791cba5-025b-45c4-9a56-948a1d6555b2 · outbound

This paper cites Staging sleep in polysomnograms: analysis of inter-scorer variability,.

Multi-task deep-learning for sleep event detection and stage classification Staging sleep in polysomnograms: analysis of inter-scorer variability,

Reference 4

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Observation 1a891cc5-48b1-4cb0-af7e-d645046fb836 · outbound

This paper cites Cesari, A.

Multi-task deep-learning for sleep event detection and stage classification Cesari, A

Reference 5

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Observation dfc22df6-5102-4c7d-a8fd-d4eaa7e672ec · outbound

This paper cites Agreement in the scoring of respiratory events and sleep among international sleep centers,.

Multi-task deep-learning for sleep event detection and stage classification Agreement in the scoring of respiratory events and sleep among international sleep centers,

Reference 6

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Observation fdf44a17-5943-4558-9435-bf2d1a322117 · outbound

This paper cites Computer-assisted analysis of polysomnographic recordings improves inter-scorer associated agreement and scoring times,.

Multi-task deep-learning for sleep event detection and stage classification Computer-assisted analysis of polysomnographic recordings improves inter-scorer associated agreement and scoring times,

Reference 7

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Source-reported events for the cited work

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Observation 8382d1b5-d84d-4a8f-80a0-8db8c3a3fbeb · outbound

This paper cites Scoring sleep with artificial intelligence enables quantification of sleep stage ambiguity: hypnodensity based on multiple expert scorers and auto-scoring,.

Multi-task deep-learning for sleep event detection and stage classification Scoring sleep with artificial intelligence enables quantification of sleep stage ambiguity: hypnodensity based on multiple expert scorers and auto-scoring,

Reference 8

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Source-reported events for the cited work

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Observation f7b1be34-334e-452b-b193-00e5a5796fc9 · outbound

This paper cites Rethinking Sleep Analysis: Comment on the AASM Manual for the Scoring of Sleep and Associated Events,.

Multi-task deep-learning for sleep event detection and stage classification Rethinking Sleep Analysis: Comment on the AASM Manual for the Scoring of Sleep and Associated Events,

Reference 9

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Source-reported events for the cited work

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Observation d352ef92-414f-4f4e-9ef3-dc9809f4ab72 · outbound

This paper cites Automatic sleep staging of EEG signals: recent development, challenges, and future directions,.

Multi-task deep-learning for sleep event detection and stage classification Automatic sleep staging of EEG signals: recent development, challenges, and future directions,

Reference 10

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Source-reported events for the cited work

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Observation 2e86bbd1-be6d-4500-bbfd-fb803b2d6123 · outbound

This paper cites Automated sleep scoring: A review of the latest approaches,.

Multi-task deep-learning for sleep event detection and stage classification Automated sleep scoring: A review of the latest approaches,

Reference 11

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Source-reported events for the cited work

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Observation 191d5a75-962c-4130-9aa9-35da9706cef9 · outbound

This paper cites A sleep apnea-hypopnea syndrome automatic detection and subtype classification method based on lstm-cnn,.

Multi-task deep-learning for sleep event detection and stage classification A sleep apnea-hypopnea syndrome automatic detection and subtype classification method based on lstm-cnn,

Reference 12

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Source-reported events for the cited work

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Observation 5236f4bf-16f8-46aa-a644-b10b47afd1e5 · outbound

This paper cites Detection of sleep apnea using deep neural networks and single-lead ecg signals,.

Multi-task deep-learning for sleep event detection and stage classification Detection of sleep apnea using deep neural networks and single-lead ecg signals,

Reference 13

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Source-reported events for the cited work

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Observation 7b3d21e4-7228-4841-96f8-bc3a25b4257a · outbound

This paper cites Detection of obstructive sleep apnea from single-channel ecg signals using a cnn-transformer architecture,.

Multi-task deep-learning for sleep event detection and stage classification Detection of obstructive sleep apnea from single-channel ecg signals using a cnn-transformer architecture,

Reference 14

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation af6859bf-4288-4374-960f-93833e254d0e · outbound

This paper cites Automatic detection of cortical arousals in sleep and their contribution to daytime sleepiness,.

Multi-task deep-learning for sleep event detection and stage classification Automatic detection of cortical arousals in sleep and their contribution to daytime sleepiness,

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation d76b8bea-81ee-49ca-98aa-a922a9dc2cdb · outbound

This paper cites Deep convolutional architecture-based hybrid learning for sleep arousal events detection through single-lead eeg signals,.

Multi-task deep-learning for sleep event detection and stage classification Deep convolutional architecture-based hybrid learning for sleep arousal events detection through single-lead eeg signals,

Reference 16

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Source-reported events for the cited work

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Observation ae6cca3d-fd9d-433a-b719-082c9ae30bce · outbound

This paper cites Detection of k-complexes in eeg signals using deep transfer learning and yolov3,.

Multi-task deep-learning for sleep event detection and stage classification Detection of k-complexes in eeg signals using deep transfer learning and yolov3,

Reference 17

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Observation 859d7236-6f5c-40e6-87d2-7ca8f65893f1 · outbound

This paper cites Expert-level sleep scoring with deep neural networks,.

Multi-task deep-learning for sleep event detection and stage classification Expert-level sleep scoring with deep neural networks,

Reference 18

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Source-reported events for the cited work

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Observation 024d1b5d-720b-4a57-9c9a-8fb3db046b4b · outbound

This paper cites Dosed: A deep learning approach to detect multiple sleep micro-events in eeg signal,.

Multi-task deep-learning for sleep event detection and stage classification Dosed: A deep learning approach to detect multiple sleep micro-events in eeg signal,

Reference 19

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Source-reported events for the cited work

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Observation cd1c965e-44e7-4f1a-a095-3e06c3949aed · outbound

This paper cites A multi-task deep learning algorithm for sleep stage scoring and sleep arousal detection,.

Multi-task deep-learning for sleep event detection and stage classification A multi-task deep learning algorithm for sleep stage scoring and sleep arousal detection,

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 0568acb6-4512-4381-ba1d-89dd6e6895bc · outbound

This paper cites Multi-task learning for arousal and sleep stage detection using fully convolutional networks,.

Multi-task deep-learning for sleep event detection and stage classification Multi-task learning for arousal and sleep stage detection using fully convolutional networks,

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 15df9394-f776-4450-a0dc-37fcd9f81b27 · outbound

This paper cites Msleepnet: A semi-supervision based multi-view hybrid neural network for simultaneous sleep arousal and sleep stage detection,.

Multi-task deep-learning for sleep event detection and stage classification Msleepnet: A semi-supervision based multi-view hybrid neural network for simultaneous sleep arousal and sleep stage detection,

Reference 22

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 37b32dbd-a940-4e45-9ba8-d3e858c3b0ce · outbound

This paper cites A deep transfer learning approach for sleep stage classification and sleep apnea detection using wrist-worn consumer sleep technologies,.

Multi-task deep-learning for sleep event detection and stage classification A deep transfer learning approach for sleep stage classification and sleep apnea detection using wrist-worn consumer sleep technologies,

Reference 23

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Source-reported events for the cited work

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Observation 4b09d2a3-c27f-4233-b00e-6aa69ed6a833 · outbound

This paper cites Msed: A multi-modal sleep event detection model for clinical sleep analysis,.

Multi-task deep-learning for sleep event detection and stage classification Msed: A multi-modal sleep event detection model for clinical sleep analysis,

Reference 24

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 10dab937-91e5-4a85-b8c4-22810c8671e9 · outbound

This paper cites Challenges of Applying Automated Polysomnography Scoring at Scale,.

Multi-task deep-learning for sleep event detection and stage classification Challenges of Applying Automated Polysomnography Scoring at Scale,

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 4d005003-fc44-4b52-8334-ab1918232346 · outbound

This paper cites You Only Look Once: Unified, Real-Time Object Detection.

Multi-task deep-learning for sleep event detection and stage classification You Only Look Once: Unified, Real-Time Object Detection

Reference 26

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Observation 51bf75c0-acba-4a4f-9b64-f267e3b7d3a5 · outbound

This paper cites A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS.

Multi-task deep-learning for sleep event detection and stage classification A Comprehensive Review of YOLO Architectures in Computer Vision: From YOLOv1 to YOLOv8 and YOLO-NAS

Reference 27

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Observation e01fdeee-8da4-45fb-b639-e58d07a8f5de · outbound

This paper cites YOLO9000: Better, Faster, Stronger.

Multi-task deep-learning for sleep event detection and stage classification YOLO9000: Better, Faster, Stronger

Reference 28

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Observation ad0bfe57-617a-4707-a558-c43472c4cd32 · outbound

This paper cites YOLOv3: An Incremental Improvement.

Multi-task deep-learning for sleep event detection and stage classification YOLOv3: An Incremental Improvement

Reference 29

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Unavailable: canonical work link unavailable.

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Observation f71d6a5c-6cad-4c6a-9147-cb2c686fdcfa · outbound

This paper cites Inter-database validation of a deep learning approach for automatic sleep scoring,.

Multi-task deep-learning for sleep event detection and stage classification Inter-database validation of a deep learning approach for automatic sleep scoring,

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 5ac53df4-a86d-4e59-9c09-a0efe5887799 · outbound

This paper cites Decentralized data-privacy preserving deep-learning approaches for enhancing inter-database generalization in automatic sleep staging,.

Multi-task deep-learning for sleep event detection and stage classification Decentralized data-privacy preserving deep-learning approaches for enhancing inter-database generalization in automatic sleep staging,

Reference 31

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 9cf6b290-6cf9-4e23-90bd-3c95be0928f5 · outbound

This paper cites The sleep heart health study: Design, rationale, and methods,.

Multi-task deep-learning for sleep event detection and stage classification The sleep heart health study: Design, rationale, and methods,

Reference 32

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation 123a3923-2b03-4d82-bc84-f5cb1a366df7 · outbound

This paper cites The national sleep research resource: towards a sleep data commons,.

Multi-task deep-learning for sleep event detection and stage classification The national sleep research resource: towards a sleep data commons,

Reference 33

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Observation fefc4c0a-fa11-44c3-982a-e82c0ad16667 · outbound

This paper cites adrania/sleep-events-detection: v0.1.1,.

Multi-task deep-learning for sleep event detection and stage classification adrania/sleep-events-detection: v0.1.1,

Reference 34

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verified fuzzy
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Observation ea159813-0ae2-4f9a-925b-9e5cabd5d827 · outbound

This paper cites A survey on multi-task learning,.

Multi-task deep-learning for sleep event detection and stage classification A survey on multi-task learning,

Reference 35

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Observation 930511c2-adc1-455a-acc1-5a6b75848e56 · outbound

This paper cites Automatic sleep stage classification with deep residual networks in a mixed-cohort setting,.

Multi-task deep-learning for sleep event detection and stage classification Automatic sleep stage classification with deep residual networks in a mixed-cohort setting,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T19:59:06.901876Z

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No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

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Pith citing papers

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