Publications of Natália Alves

2024

Papers in international journals

1. 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.
   Abstract DOI PMID
2. 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.
   Abstract DOI PMID

2023

Papers in international journals

1. 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.
   Abstract DOI PMID Cited by ~6
2. 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.
   Abstract DOI PMID Cited by ~2

Papers in conference proceedings

1. 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.
   Abstract Url

Abstracts

1. 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.
   Abstract

2022

Papers in international journals

1. 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.
   Abstract DOI Download Cited by ~31
2. 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.
   Abstract DOI Cited by ~2

Papers in conference proceedings

1. 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.
   Abstract DOI

Abstracts

1. 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.
   Abstract
2. 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.
   Abstract
3. 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.
   Abstract

2021

Abstracts

1. 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.
   Abstract