An important need exists for strategies to perform rigorous objective clinical-task-based evaluation of artificial intelligence (AI) algorithms for nuclear medicine. To address this need, we propose a four-class framework to evaluate AI algorithms for promise, technical task-specific efficacy, clinical decision making, and post-deployment efficacy. We provide best practices to evaluate AI algorithms for each of these classes. Each class of evaluation yields a claim that provides a descriptive performance of the AI algorithm. Key best practices are tabulated as the RELAINCE (Recommendations for EvaLuation of AI for NuClear medicinE) guidelines. The report was prepared by the Society of Nuclear Medicine and Molecular Imaging AI taskforce Evaluation team, which consisted of nuclear-medicine physicians, physicists, computational imaging scientists, and representatives from industry and regulatory agencies.
Pharmacology, Toxicology and Pharmaceutical Science
2
2%
Other
6
6%
Unknown
52
56%
Attention Score in Context
Attention Score in Context
This research output has an Altmetric Attention Score of 45. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 July 2025.
All research outputs
#1,171,308
of 34,457,357 outputs
Outputs from Journal of Nuclear Medicine
#261
of 8,361 outputs
Outputs of similar age
#21,988
of 469,294 outputs
Outputs of similar age from Journal of Nuclear Medicine
#11
of 69 outputs
Altmetric has tracked 34,457,357 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,361 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.9. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 469,294 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 69 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.
