22 citations · 62 across the 50 of their papers we have counts for
4 papers · 2 filters
QC-SMOTE: Quality-Controlled SMOTE for Imbalanced Classification
Parth Upman, Shreyank N Gowda
Class imbalance poses a significant challenge in classification, where existing methods such as SMOTE often generate low-quality synthetic samples in regions with noise or class ov…
Using Explainability as a Training-Time Reliability Signal for Efficient ECG Classification
Veerendhra Kumar Dangeti, Xiao Gu, Ying Weng +1
Training deep neural networks for clinical time-series analysis is computationally demanding, yet many healthcare settings lack the resources required for repeated model developmen…
Extending Pretrained 10-Second ECG Foundation Models to Longer Horizons
Wei Tang, Jinpei Han, Kangning Cui +10
Electrocardiogram (ECG) foundation models pretrained on typical diagnostic 10-second ECG segments, have demonstrated strong transferability across a range of clinical applications.…
Adaptive Data Dropout: Towards Self-Regulated Learning in Deep Neural Networks
Amar Gahir, Varshil Patel, Shreyank N Gowda
Deep neural networks are typically trained by uniformly sampling large datasets across epochs, despite evidence that not all samples contribute equally throughout learning. Recent…