It seems that appropriate methodology in the development of prediction models is becoming more common in our field. These two recent studies caught my attention: Development of a model to predict the probability of incurring a complication during spine surgery and Prediction of 90-day mortality after total hip arthroplasty. Both studies report calibration performance and […]
Tag: machine learning
Mesmerized by clinical prediction models
I am not a surgical oncologist but I came across with this study: A deep survival interpretable radiomics model of hepatocellular carcinoma patients. Authors conclude: In summary, novel deep radiomic analysis provides improved performance for risk assessment of HCC prognosis compared with Cox survival models and may facilitate stratification of HCC patients and personalization of […]
Basics of artificial intelligence and machine learning for every trainee?
This was an interesting perspective: What Should Radiology Residency and Fellowship Training in Artificial Intelligence Include? A Trainee’s Perspective—Radiology In Training. Just some take from the commentary: Trainees should be introduced to the basic concepts of data collection, annotation, and algorithm validation. AI and ML are here to stay. Hence it is important that these […]