iEDeaL: A Deep Learning Framework for Detecting Highly Imbalanced Interictal Epileptiform Discharges
Summary: iEDeaL addresses real-world, highly imbalanced IED detection rather than artificially balanced benchmarks. Its SC architecture processes raw EEG, while SaSu directly optimizes Fβ, improving accuracy and efficiency on two clinical datasets. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Qitong Wang (Université Paris Cité)
- 2. Stephen Whitmarsh (Assistance Publique–Hôpitaux de Paris; CNRS; French National Institute of Health and Medical Research; Paris Brain Institute; Pitié-Salpêtrière Hospital; Sorbonne University)
- 3. Vincent Navarro (Assistance Publique–Hôpitaux de Paris; CNRS; French National Institute of Health and Medical Research; Paris Brain Institute; Pitié-Salpêtrière Hospital; Sorbonne University)
- 4. Themis Palpanas (French University Institute; Université Paris Cité)
BibTeX Citation
@article{wang_vldb23,
title = {{iEDeaL: A Deep Learning Framework for Detecting Highly Imbalanced Interictal Epileptiform Discharges}},
author = {Wang, Qitong and Whitmarsh, Stephen and Navarro, Vincent and Palpanas, Themis},
journal = {PVLDB},
series = {{VLDB} '23},
volume = {16},
number = {3},
pages = {480--490},
doi = {10.14778/3570690.3570698},
url = {https://doi.org/10.14778/3570690.3570698},
year = {2023}
}Incoming Citations (Sorted by Pagerank)
Showing 6 of 6 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,987 | Choose Wisely: An Extensive Evaluation of Model Selection for Anomaly Detection in Time Series | 2023 | VLDB | 6.9722766e-05 |
| 6,691 | Dumpy: A Compact and Adaptive Index for Large Data Series Collections | 2023 | SIGMOD | 5.8011086e-05 |
| 9,278 | Odyssey: A Journey in the Land of Distributed Data Series Similarity Search | 2023 | VLDB | 5.2936898e-05 |
| 9,377 | LeaFi: Data Series Indexes on Steroids with Learned Filters | 2025 | SIGMOD | 5.2755515e-05 |
| 10,861 | Less is More: Efficient Time Series Dataset Condensation via Two-fold Modal Matching | 2025 | VLDB | 5.093636e-05 |
| 13,378 | ADF & TransApp: A Transformer-Based Framework for Appliance Detection Using Smart Meter Consumption Series | 2024 | VLDB | - |
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 4 of 4 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 3,869 | Smile: A System to Support Machine Learning on EEG Data at Scale | 2019 | VLDB | 7.0609879e-05 |
| 5,231 | Hercules Against Data Series Similarity Search | 2022 | VLDB | 6.3068064e-05 |
| 6,691 | Dumpy: A Compact and Adaptive Index for Large Data Series Collections | 2023 | SIGMOD | 5.8011086e-05 |
| 9,479 | dCAM: Dimension-wise Class Activation Map for Explaining Multivariate Data Series Classification | 2022 | SIGMOD | 5.2634238e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 3,423 | Computing Graph Edit Distance via Neural Graph Matching | 2023 | VLDB |
| 2 | 10,800 | Two Birds with One Stone: Efficient Deep Learning over Mislabeled Data through Subset Selection | 2025 | SIGMOD |
| 3 | 11,099 | MLP-Mixer based Masked Autoencoders Are Effective, Explainable and Robust for Time Series Anomaly Detection | 2025 | VLDB |
| 4 | 4,905 | Medical Entity Disambiguation Using Graph Neural Networks | 2021 | SIGMOD |
| 5 | 6,074 | Automatic Data Acquisition for Deep Learning | 2021 | VLDB |
| 6 | 2,475 | Deep Learning for Blocking in Entity Matching: A Design Space Exploration | 2021 | VLDB |
| 7 | 8,979 | Cerebro: A Layered Data Platform for Scalable Deep Learning | 2021 | CIDR |
| 8 | 8,824 | DLACEP: A Deep-Learning Based Framework for Approximate Complex Event Processing | 2022 | SIGMOD |
| 9 | 6,115 | Fine-grained Concept Linking using Neural Networks in Healthcare | 2018 | SIGMOD |
| 10 | 3,869 | Smile: A System to Support Machine Learning on EEG Data at Scale | 2019 | VLDB |