Update README.md

README.md

@@ -11,10 +11,15 @@ In this project, we benchmarked various machine learning (ML) approaches for det
 
 ## Models
 
+We are releasing the weights for the three best-performing models:
 
+- **S4-ECG:** A Structured State Space model well-suited to ECG waveforms, capturing both local and long-range temporal features for robust ACS detection. Building upon work by [Strodthoff et al.](https://github.com/AI4HealthUOL/ECG-MIMIC).
+- **ResNet-18:** A 1D convolutional residual network adapted for ECG data, leveraging skip connections to learn complex patterns without vanishing gradients.
+- **HuBERT-ECG:** A transformer-based architecture originally designed for speech recognition, repurposed and fine-tuned on ECG signals for ACS prediction. Based on work by [Coppola et al.](https://github.com/Edoar-do/HuBERT-ECG/tree/master/code).
 
 ## Usage
 
 
+
 ## Citation