Human-like few-shot and one-shot learning of the electrocardiograms: an empirical study investigating the use of a pseudo-coloring technique to improve and explain machine vision predictions of long QT syndrome
Fuente:
Zenodo
Saved in:
| Main Author: | Alahmadi, Alaa |
|---|---|
| Format: | Recurso digital |
| Published: |
Zenodo
2025
|
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Human-like visual computing advances explainability and few-shot learning in deep neural networks for complex physiological data
by: Alahmadi, Alaa, et al.
Published: (2025)
by: Alahmadi, Alaa, et al.
Published: (2025)
When predict can also explain: few-shot prediction to select better neural latents
by: Dabholkar, Kabir, et al.
Published: (2024)
by: Dabholkar, Kabir, et al.
Published: (2024)
An open‐source general purpose machine learning framework for individual animal re‐identification using few‐shot learning
by: Oscar Wahltinez, et al.
Published: (2024)
by: Oscar Wahltinez, et al.
Published: (2024)
Fetal electrocardiogram prediction using machine learning: a random forest-based approach
by: Moutaib, Mohammed, et al.
Published: (2024)
by: Moutaib, Mohammed, et al.
Published: (2024)
Dynamical cross-correlations between RR and QT intervals in long-term electrocardiogram recordings
by: Kokkonen, Jimi, et al.
Published: (2024)
by: Kokkonen, Jimi, et al.
Published: (2024)
Music auto-tagging in the long tail: A few-shot approach
by: Ma, T. Aleksandra, et al.
Published: (2024)
by: Ma, T. Aleksandra, et al.
Published: (2024)
Demonstration-based learning for few-shot biomedical named entity recognition under machine reading comprehension
by: Su, Leilei, et al.
Published: (2023)
by: Su, Leilei, et al.
Published: (2023)
Spatial frequency information fusion network for few-shot learning
by: Zhao, Wenqing, et al.
Published: (2025)
by: Zhao, Wenqing, et al.
Published: (2025)
Multi-task and few-shot learning in virtual flow metering
by: Løvland, Kristian, et al.
Published: (2023)
by: Løvland, Kristian, et al.
Published: (2023)
Vocabulary-free few-shot learning for Vision-Language Models
by: Zanella, Maxime, et al.
Published: (2025)
by: Zanella, Maxime, et al.
Published: (2025)
Single-shot quantum machine learning
by: Recio-Armengol, Erik, et al.
Published: (2024)
by: Recio-Armengol, Erik, et al.
Published: (2024)
Structured Output Regularization: a framework for few-shot transfer learning
by: Ewen, Nicolas, et al.
Published: (2025)
by: Ewen, Nicolas, et al.
Published: (2025)
Visually grounded few-shot word learning in low-resource settings
by: Nortje, Leanne, et al.
Published: (2023)
by: Nortje, Leanne, et al.
Published: (2023)
Multitask frame-level learning for few-shot sound event detection
by: Zou, Liang, et al.
Published: (2024)
by: Zou, Liang, et al.
Published: (2024)
Initialization matters in few-shot adaptation of vision-language models for histopathological image classification
by: Meseguer, Pablo, et al.
Published: (2026)
by: Meseguer, Pablo, et al.
Published: (2026)
Investigating grammatical abstraction in language models using few-shot learning of novel noun gender
by: Sukumaran, Priyanka, et al.
Published: (2024)
by: Sukumaran, Priyanka, et al.
Published: (2024)
Reading ability detection using eye-tracking data with LSTM-based few-shot learning
by: Li, Nanxi, et al.
Published: (2024)
by: Li, Nanxi, et al.
Published: (2024)
Multiscale attention for few‐shot image classification
by: Tong Zhou, et al.
Published: (2024)
by: Tong Zhou, et al.
Published: (2024)
FSL-CP: a benchmark for small molecule activity few-shot prediction using cell microscopy images
by: Ha, Son V., et al.
Published: (2024)
by: Ha, Son V., et al.
Published: (2024)
Scaling few-shot spoken word classification with generative meta-continual learning
by: Beyers, Louise, et al.
Published: (2026)
by: Beyers, Louise, et al.
Published: (2026)
Explainable few-shot learning workflow for detecting invasive and exotic tree species
by: Gevaert, Caroline M., et al.
Published: (2024)
by: Gevaert, Caroline M., et al.
Published: (2024)
The representation landscape of few-shot learning and fine-tuning in large language models
by: Doimo, Diego, et al.
Published: (2024)
by: Doimo, Diego, et al.
Published: (2024)
Statistical few-shot learning for large-scale classification via parameter pooling
by: Simpson, Andrew, et al.
Published: (2025)
by: Simpson, Andrew, et al.
Published: (2025)
Generalized few-shot transfer learning architecture for modeling the EDFA gain spectrum
by: Raj, Agastya, et al.
Published: (2025)
by: Raj, Agastya, et al.
Published: (2025)
Brain-inspired analogical mixture prototypes for few-shot class-incremental learning
by: Li, Wanyi, et al.
Published: (2025)
by: Li, Wanyi, et al.
Published: (2025)
Expanding continual few-shot learning benchmarks to include recognition of specific instances
by: Kowadlo, Gideon, et al.
Published: (2022)
by: Kowadlo, Gideon, et al.
Published: (2022)
Explainable machine learning for neoplasms diagnosis via electrocardiograms: an externally validated study
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)
by: Alcaraz, Juan Miguel Lopez, et al.
Published: (2024)
Combination of dynamic TOPMODEL and machine learning techniques to improve runoff prediction
by: Pin‐Chun Huang
Published: (2024)
by: Pin‐Chun Huang
Published: (2024)
Holter study of heart rate variability in children and adolescents with long QT syndrome
by: Anna Lundström, et al.
Published: (2024)
by: Anna Lundström, et al.
Published: (2024)
Active perception and disentangled representations allow continual, episodic zero and few-shot learning
by: Rawlinson, David, et al.
Published: (2026)
by: Rawlinson, David, et al.
Published: (2026)
Identifying type II quasars at intermediate redshift with few-shot learning photometric classification
by: Cunha, P. A. C., et al.
Published: (2024)
by: Cunha, P. A. C., et al.
Published: (2024)
MetaChest: Generalized few-shot learning of pathologies from chest X-rays
by: Montalvo-Lezama, Berenice, et al.
Published: (2025)
by: Montalvo-Lezama, Berenice, et al.
Published: (2025)
Adaptive few-shot learning for robust part quality classification in two-photon lithography
by: Jia, Sixian, et al.
Published: (2026)
by: Jia, Sixian, et al.
Published: (2026)
Towards few-shot isolated word reading assessment
by: Smit, Reuben, et al.
Published: (2025)
by: Smit, Reuben, et al.
Published: (2025)
Double‐device therapy in a patient with long QT syndrome
by: Shohei Kataoka, et al.
Published: (2024)
by: Shohei Kataoka, et al.
Published: (2024)
REX: Causal discovery based on machine learning and explainability techniques
by: Renero, Jesus, et al.
Published: (2025)
by: Renero, Jesus, et al.
Published: (2025)
Verifying a stabilizer state with few observables but many shots
by: Theis, Dirk Oliver
Published: (2024)
by: Theis, Dirk Oliver
Published: (2024)
The shape of the brain's connections is predictive of cognitive performance: an explainable machine learning study
by: Lo, Yui, et al.
Published: (2024)
by: Lo, Yui, et al.
Published: (2024)
Scalable and consistent few-shot classification of survey responses using text embeddings
by: Mjaaland, Jonas Timmann, et al.
Published: (2025)
by: Mjaaland, Jonas Timmann, et al.
Published: (2025)
Early prediction of transfusion requirements in trauma patients using explainable machine learning
by: Michael R. De La Rosa, et al.
Published: (2026)
by: Michael R. De La Rosa, et al.
Published: (2026)
Similar Items
-
Human-like visual computing advances explainability and few-shot learning in deep neural networks for complex physiological data
by: Alahmadi, Alaa, et al.
Published: (2025) -
When predict can also explain: few-shot prediction to select better neural latents
by: Dabholkar, Kabir, et al.
Published: (2024) -
An open‐source general purpose machine learning framework for individual animal re‐identification using few‐shot learning
by: Oscar Wahltinez, et al.
Published: (2024) -
Fetal electrocardiogram prediction using machine learning: a random forest-based approach
by: Moutaib, Mohammed, et al.
Published: (2024) -
Dynamical cross-correlations between RR and QT intervals in long-term electrocardiogram recordings
by: Kokkonen, Jimi, et al.
Published: (2024)