Filippo Ruffini
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View article: Benchmarking foundation models and parameter-efficient fine-tuning for prognosis prediction in medical imaging
Benchmarking foundation models and parameter-efficient fine-tuning for prognosis prediction in medical imaging Open
View article: Doctor-in-the-Loop: An explainable, multi-view deep learning framework for predicting pathological response in non-small cell lung cancer
Doctor-in-the-Loop: An explainable, multi-view deep learning framework for predicting pathological response in non-small cell lung cancer Open
View article: Benchmarking Foundation Models and Parameter-Efficient Fine-Tuning for Prognosis Prediction in Medical Imaging
Benchmarking Foundation Models and Parameter-Efficient Fine-Tuning for Prognosis Prediction in Medical Imaging Open
Despite the significant potential of Foundation Models (FMs) in medical imaging, their application to prognosis prediction remains challenging due to data scarcity, class imbalance, and task complexity, which limit their clinical adoption.…
View article: Text-to-CT Generation via 3D Latent Diffusion Model with Contrastive Vision-Language Pretraining
Text-to-CT Generation via 3D Latent Diffusion Model with Contrastive Vision-Language Pretraining Open
Objective: While recent advances in text-conditioned generative models have enabled the synthesis of realistic medical images, progress has been largely confined to 2D modalities such as chest X-rays. Extending text-to-image generation to …
View article: Machine Learning for Predicting the Low Risk of Postoperative Pancreatic Fistula After Pancreaticoduodenectomy: Toward a Dynamic and Personalized Postoperative Management Strategy
Machine Learning for Predicting the Low Risk of Postoperative Pancreatic Fistula After Pancreaticoduodenectomy: Toward a Dynamic and Personalized Postoperative Management Strategy Open
Background. Postoperative pancreatic fistula (POPF) remains one of the most relevant complications following pancreaticoduodenectomy (PD), significantly impacting short-term outcomes and delaying adjuvant therapies. Current predictive mode…
View article: A systematic review of intermediate fusion in multimodal deep learning for biomedical applications
A systematic review of intermediate fusion in multimodal deep learning for biomedical applications Open
Deep learning has revolutionized biomedical research by providing sophisticated methods to handle complex, high-dimensional data. Multimodal deep learning (MDL) further enhances this capability by integrating diverse data types such as ima…
View article: Doctor-in-the-Loop: An Explainable, Multi-View Deep Learning Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer
Doctor-in-the-Loop: An Explainable, Multi-View Deep Learning Framework for Predicting Pathological Response in Non-Small Cell Lung Cancer Open
Non-small cell lung cancer (NSCLC) remains a major global health challenge, with high post-surgical recurrence rates underscoring the need for accurate pathological response predictions to guide personalized treatments. Although artificial…
View article: A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications
A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications Open
View article: A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications
A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications Open
Deep learning has revolutionized biomedical research by providing sophisticated methods to handle complex, high-dimensional data. Multimodal deep learning (MDL) further enhances this capability by integrating diverse data types such as ima…
View article: Multi-Dataset Multi-Task Learning for COVID-19 Prognosis
Multi-Dataset Multi-Task Learning for COVID-19 Prognosis Open
In the fight against the COVID-19 pandemic, leveraging artificial intelligence to predict disease outcomes from chest radiographic images represents a significant scientific aim. The challenge, however, lies in the scarcity of large, label…
View article: A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications
A Systematic Review of Intermediate Fusion in Multimodal Deep Learning for Biomedical Applications Open