Whole Slide Image-Based Weakly Supervised Deep Learning for Predicting Major Pathological Response in Non-Small Cell Lung Cancer Following Neoadjuvant Chemoimmunotherapy ： a Multicenter, Retrospective, Cohort Study
This research output has an Altmetric Attention Score of 1. 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 01 September 2024.
All research outputs
#23,860,888
of 26,558,784 outputs
Outputs from Frontiers in immunology
#28,870
of 33,376 outputs
Outputs of similar age
#111,146
of 143,821 outputs
Outputs of similar age from Frontiers in immunology
#269
of 394 outputs
Altmetric has tracked 26,558,784 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 33,376 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.6. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 143,821 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 394 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
