In this project, I built a deep-learning model using audio data collected from early preterm neonates in the NICU. Using labels obtained from Echocardiography for the diagnosis of PDA. This project can help in early, non-invasive detection of PDA, leading to timely interventions and better outcomes for preterm neonates. Subsequently, we converted these audio data into spectrograms and classified them using deep learning algorithms as either having PDA or not PDA. Currently, we have reached two hundred patients and the data collection process is ongoing. We will continue expanding our dataset to improve the model’s robustness and reliability.
