Artificial intelligence-assisted double reading of chest radiographs to detect clinically relevant missed findings: a two-centre evaluation - Top-Institutions - MDSpire

Artificial intelligence-assisted double reading of chest radiographs to detect clinically relevant missed findings: a two-centre evaluation

  • By

  • Laurens Topff

  • Sanne Steltenpool

  • Erik R. Ranschaert

  • Naglis Ramanauskas

  • Renee Menezes

  • Jacob J. Visser

  • Regina G. H. Beets-Tan

  • Nolan S. Hartkamp

  • March 11, 2024

  • 0 min

Share

Top Institutions in Radiology

Brief introduction explaining scope and methodology.

  • #1

    Massachusetts General Hospital
    Massachusetts General Hospital

    Boston, MA

    Key Differentiators

    • Radiology
    • Artificial Intelligence
    • Pulmonology

  • #2

    Stanford University Medical Center
    Stanford University Medical Center

    Stanford, CA

    Key Differentiators

    • Radiology
    • Biomedical Informatics
    • Artificial Intelligence

  • #3

    Johns Hopkins Hospital
    Johns Hopkins Hospital

    Baltimore, MD

    Key Differentiators

    • Radiology
    • Artificial Intelligence
    • Pulmonary Medicine

  • #4

    Mayo Clinic
    Mayo Clinic

    Rochester, MN

    Key Differentiators

    • Radiology
    • Artificial Intelligence
    • Pulmonology

  • #5

    University of California, San Francisco (UCSF) Medical Center
    University of California, San Francisco (UCSF) Medical Center

    San Francisco, CA

    Key Differentiators

    • Radiology
    • Artificial Intelligence
    • Pulmonary Medicine

Original Source(s)

Artificial intelligence-assisted double reading of chest radiographs to detect clinically relevant missed findings: a two-centre evaluation

  • by Laurens Topff, Sanne Steltenpool, Erik R. Ranschaert, Naglis Ramanauskas, Renee Menezes, Jacob J. Visser, Regina G. H. Beets-Tan, Nolan S. Hartkamp

  • March 11, 2024

Related Content

3D intratumoral heterogeneity-based quantitative score from chest CT for preoperative prediction of visceral pleural invasion in lung adenocarcinoma: a multicenter study

Quality over quantity: biopsy-anchored CT radiogenomics models outperform all-lesion training in a multi-tumour cohort despite a smaller sample size

Steroids Found to Limit Effectiveness of Lung Cancer Immunotherapy Treatment

Keck Medicine of USC researchers discovered that tumors shrank less in patients who were given steroids for symptoms of lung cancer.

  • by

  • March 8, 2026

  • 7 min