A deep learning-based multimodal data fusion algorithm for predicting checkpoint inhibitors related pneumonia

Key Points

• Predictive modeling approaches show a significant capability for anticipating pneumonia incidence with this algorithm.
• The model achieves high accuracy rates, specifically predicting over 85% of pneumonia cases related to treatment.
• Deep learning-based multimodal data fusion combines various data types for improved prediction outcomes.
• These findings highlight the importance of integrating multiple data sources to enhance predictive capabilities.