- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
AI & Medical Imaging: The Ethical Issues, Pt. 3
What other ethical questions exist, and what the future holds.
The use of artificial intelligence (AI) in medical imaging is not new – in fact, it has been a topic of conversation at the Radiological Society of North America (RSNA) annual meeting for at least the past five years. And, with that continued growth comes the obligation among radiologists to approach its use in medical imaging in the most ethical ways possible.
On Monday, radiology ethics expert David Larson, M.D., professor radiology at Stanford University, discussed how data used in AI tools are now being applied to clinical care. That information holds tremendous value, but the industry does not yet have the ethical, regulatory, and legal constructs in place to ensure the data is handled in the most proper fashion.
In part three of this video series, Larson talks with Diagnostic Imaging about the other ethical questions that exist, along with potential safeguards that can be implemented, as well as what the future holds if these ethical questions are not answered appropriately.
For more RSNA coverage, click here.
Mammography Study Suggests DBT-Based AI May Help Reduce Disparities with Breast Cancer Screening
December 13th 2024New research suggests that AI-powered assessment of digital breast tomosynthesis (DBT) for short-term breast cancer risk may help address racial disparities with detection and shortcomings of traditional mammography in women with dense breasts.
The Reading Room Podcast: Emerging Trends in the Radiology Workforce
February 11th 2022Richard Duszak, MD, and Mina Makary, MD, discuss a number of issues, ranging from demographic trends and NPRPs to physician burnout and medical student recruitment, that figure to impact the radiology workforce now and in the near future.
Can MRI-Based AI Bolster Biopsy Decision-Making in PI-RADS 3 Cases?
December 9th 2024In patients with PI-RADS 3 lesion assessments, the combination of AI and prostate-specific antigen density (PSAD) level achieved a 78 percent sensitivity and 93 percent negative predictive value for clinically significant prostate cancer (csPCa), according to research presented at the Radiological Society of North American (RSNA) conference.
