Publications of Colin Jacobs

all all years 2024 2023 2022 2021 2020 2019 2018 2017 2016 2015 2014 2013 2012 and before

2024

Papers in international journals

  1. I. van den Berk, C. Jacobs, M. Kanglie, O. Mets, M. Snoeren, A. van Montauban Swijndregt, E. Taal, T. van Engelen, J. Prins, S. Bipat, P. Bossuyt, J. Stoker, T. study group, J. Annema, L. Beenen, D. Bekebrede-Kaufman, I. van den Berk, P. Bossuyt, B. Elzer, T. van Engelen, B. Frankemölle, M. Groenink, E. Hoolwerf, D. Hulzebosch, M. Kanglie, S. Kolkman, N. Lobe, P. Leenhouts, O. Mets, M. Monraats, J. Luitse, S. Middeldorp, A. van Swijndregt, J. Otker, A. van Randen, M. Ridderikhof, J. Romijn, M. Scheerder, A. Schoonderwoerd, L. Schijf, F. Smithuis, J. Stoker, G. Streekstra, E. Taal, G. de Vries, M. Vogel and I. Yahya, "An AI deep learning algorithm for detecting pulmonary nodules on ultra-low-dose CT in an emergency setting: a reader study", European Radiology Experimental, 2024;8.
    Abstract DOI PMID
  2. D. Zhong, G. Sidorenkov, C. Jacobs, P. de Jong, H. Gietema, R. Stadhouders, K. Nackaerts, J. Aerts, M. Prokop, H. Groen, G. de Bock, R. Vliegenthart, M. Heuvelmans and S. Atzen, "Lung Nodule Management in Low-Dose CT Screening for Lung Cancer: Lessons from the NELSON Trial", Radiology, 2024;313.
    Abstract DOI PMID
  3. 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
  4. E. Sogancioglu, B. van Ginneken, F. Behrendt, M. Bengs, A. Schlaefer, M. Radu, D. Xu, K. Sheng, F. Scalzo, E. Marcus, S. Papa, J. Teuwen, E. Scholten, S. Schalekamp, N. Hendrix, C. Jacobs, W. Hendrix, C. Sánchez and K. Murphy, "Nodule detection and generation on chest X-rays: NODE21 Challenge", IEEE Transactions on Medical Imaging, 2024;43(8):2839-2853.
    Abstract DOI PMID
  5. L. Boulogne, J. Charbonnier, C. Jacobs, E. van der Heijden and B. van Ginneken, "Estimating lung function from computed tomography at the patient and lobe level using machine learning", Medical Physics, 2024;51:2834-2845.
    Abstract DOI PMID
  6. C. Jacobs, "Decoding pulmonary nodules: can machine learning enhance malignancy risk stratification?", Thorax, 2024;79:293-294.
    Abstract DOI PMID
  7. C. Ferreira, K. Venkadesh, C. Jacobs, M. Coimbra and A. Campilho, "Towards automatic forecasting of lung nodule diameter with tabular data and CT imaging", Biomedical Signal Processing and Control, 2024;96:106625.
    Abstract DOI
  8. W. Xie, C. Jacobs, J. Charbonnier and B. van Ginneken, "Structure and position-aware graph neural network for airway labeling", Medical Image Analysis, 2024;97:103286.
    Abstract DOI Cited by ~5

Abstracts

  1. F. van der Graaf, N. Antonissen, E. Scholten, M. Prokop and C. Jacobs, "Assessing the agreement between privacy-preserving Llama model and human experts when labelling radiology reports for specific significant incidental findings in lung cancer screening", Annual Meeting of the European Society of Thoracic Imaging, 2024.
    Abstract
  2. F. van der Graaf, N. Antonissen, Z. Saghir, M. Prokop and C. Jacobs, "External validation of the Sybil risk model as a tool to identify low-risk individuals eligible for biennial lung cancer screening", European Congress of Radiology, 2024.
    Abstract
  3. B. Obreja, K. Venkadesh, W. Hendrix, Z. Saghir, M. Prokop and C. Jacobs, "Deep Learning for estimating pulmonary nodule malignancy risk: How much data does AI need to reach radiologist level performance?", European Congress of Radiology, 2024.
    Abstract
  4. M. Vitale, M. Boenink, M. Vegter and C. Jacobs, "Norms for Responsible AI-enabled Population Screening", European Society for Philosophy of Medicine and Healthcare, 2024.
    Abstract
  5. R. Dinnessen, K. Venkadesh, D. Peeters, H. Gietema, E. Scholten, C. Schaefer-Prokop and C. Jacobs, "External validation of an AI algorithm for pulmonary nodule malignancy risk estimation on a dataset of incidentally detected pulmonary nodules", European Congress of Radiology, 2024.
    Abstract
  6. N. Antonissen, K. Venkadesh, H. Gietema, R. Vliegenthart, Z. Saghir, E. Scholten, M. Prokop, C. Schaefer-Prokop and C. Jacobs, "Retrospective validation and comparison of deep learning based risk thresholds versus growth-centric protocols in pulmonary nodule assessment in screening", Annual Meeting of the European Society of Thoracic Imaging, 2024.
    Abstract
  7. D. Peeters, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, R. Vliegenthart, M. Prokop and C. Jacobs, "Towards safe and reliable implementation of AI models for nodule malignancy estimation using distance-based out-of-distribution detection", Annual Meeting of the European Society of Thoracic Imaging, 2024.
    Abstract

PhD theses

  1. K. Venkadesh, "AI for lung cancer screening", PhD thesis, 2024.
    Abstract Url
  2. G. Humpire-Mamani, "Deep Learning for Localization and Segmentation in Thorax Abdomen CT", PhD thesis, 2024.
    Abstract Url
  3. W. Hendrix, "Artificial Intelligence for Detection of Lung and Airway Nodules in Clinical Chest CT scans", PhD thesis, 2024.
    Abstract Url