Biometric Contrastive Learning for Data-Efficient Deep Learning from Electrocardiographic Images.
Veer SanghaAkshay KhunteGregory HolsteBobak J MortazaviZhangyang WangEvangelos K OikonomouRohan KheraPublished in: medRxiv : the preprint server for health sciences (2023)
A pretraining strategy that leverages biometric signatures of different ECGs from the same patient enhances the efficiency of developing AI models for ECG images. This represents a major advance in detecting disorders from ECG images with limited labeled data.
Keyphrases
- deep learning
- artificial intelligence
- convolutional neural network
- big data
- electronic health record
- heart rate variability
- machine learning
- optical coherence tomography
- heart rate
- case report
- genome wide
- heart failure
- gene expression
- blood pressure
- dna methylation
- data analysis
- positron emission tomography
- atrial fibrillation