Camillo Maria Caruso

Full profile and recent publications of Camillo Maria Caruso.

Camillo Maria Caruso

Researcher

Camillo Maria Caruso

Postdoctoral Researcher @ Università Campus Bio-Medico di Roma

Camillo M. Caruso is a researcher with a Ph.D. in AI, designing and building multimodal deep-learning systems that turn heterogeneous clinical data, imaging, tabular records, free text, into actionable tools for diagnosis, prognosis, and treatment support, with a particular focus on learning robustly from incomplete information. He earned his Ph.D. at University Campus Bio-Medico of Rome, where he developed transformer-based architectures resilient to missing data for classification and time-to-event prediction tasks, publishing in venues such as AI Open, Computers in Biology and Medicine, and IEEE Access, and making his research publicly available as open source.

Multimodal Learning Deep Learning Computer Vision

Recent Publications

  1. Retrieval-Augmented Anatomical Guidance for Text-to-CT Generation
    arXiv preprint arXiv:2603.08305, 2026
  2. Not another imputation method: A transformer-based model for missing values in tabular datasets
    2026
  3. Learning from Limited and Incomplete Data: A Multimodal Framework for Predicting Pathological Response in NSCLC
    arXiv preprint arXiv:2603.15100, 2026
  4. Handling Missing Modalities in Multimodal Survival Prediction for Non-Small Cell Lung Cancer
    2026
  5. Text-to-CT Generation via 3D Latent Diffusion Model with Contrastive Vision-Language Pretraining
    arXiv preprint arXiv:2506.00633, 2025
  6. Next-Gen Health: from Multimodal AI to Foundation Models
    2025
  7. MARIA: A multimodal transformer model for incomplete healthcare data
    2025
  8. Long-term outcomes from pembrolizumab monotherapy in patients with advanced NSCLC, PD-L1 expression ≥ 50 %, and poor performance status: Transformer-based AI to characterize prognostic complexity
    2025
  9. Leveraging MIMIC Datasets for Better Digital Health: A Review on Open Problems, Progress Highlights, and Future Promises
    arXiv preprint arXiv:2506.12808, 2025
  10. A systematic review of intermediate fusion in multimodal deep learning for biomedical applications
    2025