If a radiologist missed a key finding but AI software didn’t, how would a jury determine legal culpability? Researchers from Brown University recently explored that question and came up with some interesting findings.
After surveying hundreds of jurors, the study team concluded that although that scenario would negatively affect the defense, the effect could be substantially mitigated by providing the panel with data on the algorithm’s error rates. Discover what else they concluded in our most highly viewed article this week.
In a new study, PET has found sex-related differences in the brains of those with alcohol use disorder. Women had significantly lower levels of protein involved in the brain’s immune response, according to the authors.
Other popular stories this week included reports on how AI-directed breast MRI could yield shorter scan times, how an explainable deep-learning model could aid in diagnosis of liver cancer, and how radiology AI saves time in a clinical setting. In addition, learn how technology-enabled interventions were able to help reduce unnecessary recommendations for additional imaging.
Finally, we’re also excited to launch SalaryScan, our annual initiative that provides our members with the latest data on compensation and benefits in radiology. Please take a few minutes now to fill out this short survey. As always, your responses will be kept totally anonymous and will help to produce the most accurate results.
See below for the full list of our top stories of the week:
If AI finds an abnormality that a radiologist misses, who’s at fault?
PET reveals differences in people with alcohol abuse disorder
AI-directed breast MRI scanning may lead to shorter scan times
Explainable DL MRI model shows promise diagnosing liver cancer
Interventions help reduce additional wasteful imaging recommendations
MRI-based fusion model determines HER2 status in breast cancer
Chemotherapy negatively affects women’s cognitive function
Researchers urge better LCS for smokers with mental health conditions
AI model saves time in live radiology clinical practice setting
IMV: patient satisfaction tops mammography department priorities
