AI Provides Hope to Improve the Efficiency of Breast Radiologists

This publication has 8 references indexed in Scilit:

• Impact of slab thickness in digital breast tomosynthesis on radiologists’ diagnostic accuracy and interpretation time in women with breast cancer: a single-center retrospective study
  Quantitative Imaging in Medicine and Surgery, 2025
• Breast Imaging Staffing Shortages: Defining the Problem and Addressing Root Causes
  Journal of Breast Imaging, 2025
• Enhancing Radiologist Reading Performance by Ordering Screening Mammograms Based on Characteristics That Promote Visual Adaptation
  Radiology, 2024
• How long does it take to read a mammogram? Investigating the reading time of digital breast tomosynthesis and digital mammography
  European Journal of Radiology, 2024
• Impact of AI for Digital Breast Tomosynthesis on Breast Cancer Detection and Interpretation Time
  Radiology: Artificial Intelligence, 2024
• Historical control
  2023
• Performance of Digital Breast Tomosynthesis, Synthetic Mammography, and Digital Mammography in Breast Cancer Screening: A Systematic Review and Meta-Analysis
  JNCI: Journal of the National Cancer Institute, 2020
• Common pitfalls in statistical analysis: Clinical versus statistical significance
  Perspectives in Clinical Research, 2015