Automated Classification of Store‐Operated Calcium Entry Activity and Disease Conditions in Murine Skeletal Muscle Images Using Machine Learning

Key Points

• Classifying store-operated calcium entry activity can transform clinical approaches to muscle pathologies, improving diagnosis.
• Convolutional neural networks and support vector machines effectively analyze muscle images with promising accuracy.
• Assessment evaluates tissue classification automation, indicating potential for scaling in diverse clinical applications.
• Exploration of larger datasets and advanced techniques, like transformer models, may enhance analysis for complex conditions.