Publications of Natália Alves
Papers in international journals
- D. Peeters, N. Alves, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, C. Schaefer-Prokop, R. Vliegenthart, M. Prokop and C. Jacobs, "Enhancing a deep learning model for pulmonary nodule malignancy risk estimation in chest CT with uncertainty estimation", European Radiology, 2024.
- T. Perik, N. Alves, J. Hermans and H. Huisman, "Automated Quantitative Analysis of CT Perfusion to Classify Vascular Phenotypes of Pancreatic Ductal Adenocarcinoma", Cancer, 2024;16(3):577.
- N. Alves, J.S. Bosma, K. Venkadesh, C. Jacobs, Z. Saghir, M. de Rooij, J. Hermans and H. Huisman, "Prediction Variability to Identify Reduced AI Performance in Cancer Diagnosis at MRI and CT", Radiology, 2023;308(3):e230275.
- M. Schuurmans, N. Alves, P. Vendittelli, H. Huisman and J. Hermans, "Artificial Intelligence in Pancreatic Ductal Adenocarcinoma Imaging: A Commentary on Potential Future Applications.", Gastroenterology, 2023.
- N. Alves, M. Schuurmans, G. Litjens, J.S. Bosma, J. Hermans and H. Huisman, "Fully Automatic Deep Learning Framework for Pancreatic Ductal Adenocarcinoma Detection on Computed Tomography", Cancers, 2022:376.
- M. Schuurmans, N. Alves, P. Vendittelli, H. Huisman and J. Hermans, "Setting the Research Agenda for Clinical Artificial Intelligence in Pancreatic Adenocarcinoma Imaging", Cancers, 2022:3498.
Papers in conference proceedings
- J.S. Bosma, D. Peeters, N. Alves, A. Saha, Z. Saghir, C. Jacobs and H. Huisman, "Reproducibility of Training Deep Learning Models for Medical Image Analysis", Medical Imaging with Deep Learning, 2023.
- N. Alves and B. de Wilde, "Uncertainty-Guided Self-learning Framework for Semi-supervised Multi-organ Segmentation", Fast and Low-Resource Semi-supervised Abdominal Organ Segmentation, 2022:116-127.
Abstracts
- D. Peeters, N. Alves, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, H. Huisman, C. Schaefer-Prokop, R. Vliegenthart, M. Prokop and C. Jacobs, "The effect of applying an uncertainty estimation method on the performance of a deep learning model for nodule malignancy risk estimation", European Congress of Radiology, 2023.
- J.S. Bosma, N. Alves and H. Huisman, "Performant and Reproducible Deep Learning Based Cancer Detection Models for Medical Imaging", Annual Meeting of the Radiological Society of North America, 2022.
- S. de Jong, N. Alves, M. Schuurmans, J. Hermans and H. Huisman, "Deep Learning for Automatic Contrast Enhancement Phase Detection on Abdominal Computed Tomography", Annual Meeting of the Radiological Society of North America, 2022.
- N. Alves, J.S. Bosma and H. Huisman, "Towards Safe Clinical Use of Artificial Intelligence for Cancer Detection Through Uncertainty Quantification", Annual Meeting of the Radiological Society of North America, 2022.
- N. Alves, J. Hermans and H. Huisman, "CT-based Deep Learning Towards Early Detection Of Pancreatic Ductal Adenocarcinoma", Annual Meeting of the Radiological Society of North America, 2021.