Jurors are more likely to find radiologists at fault if AI detects an abnormality they miss, but transparency about AI error rates can mitigate this effect.
Key Details
- 1Study evaluated over 1,300 mock jurors using vignettes of missed brain bleeds or cancer diagnoses.
- 2Jurors sided with plaintiffs 72.9% (brain bleed) and 78.7% (cancer) when AI flagged missed findings, versus 56.3% and 65.2% with no AI.
- 3Disclosure of AI's false omission (1%) or false discovery (50%) rates reduced perceived radiologist liability.
- 4If both radiologist and AI missed abnormality, jurors were less likely to fault the radiologist (50% for brain bleed, 63.5% for cancer).
- 5Providing AI error rates had stronger mitigating effects for brain bleed cases than for cancer.
Why It Matters
As AI tools become more integrated into radiology workflows, awareness of their error profiles and transparent communication may have significant legal implications. The findings can inform how radiologists document and present AI results to reduce liability risk in diagnostic misses.
Source
AuntMinnie
Related News
•AuntMinnie
AI Enables Safe 75% Gadolinium Reduction in Breast MRI Without Losing Sensitivity
AI-enhanced breast MRI with a 75% reduced gadolinium dose maintained diagnostic sensitivity comparable to full-dose protocols.
•Cardiovascular Business
Deep Learning AI Model Detects Coronary Microvascular Dysfunction Via ECG
A new AI algorithm rapidly detects coronary microvascular dysfunction using ECGs, with validation incorporating PET imaging.
•AuntMinnie
Study: Patients Prefer AI in Radiology as Assistive, Not Standalone Tool
Survey finds patients support AI-assisted radiology but not AI-only interpretations.