Article metrics for:
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
Last updated: Sat, 24 Feb 2018 06:15:39 GMT
Altmetric score (what's this?)
- Tweeted by 188
- Blogged by 5
- On 5 Facebook pages
- Mentioned in 1 Google+ posts
- Picked up by 17 news outlets
- 2 Reddit
- 199 readers on Mendeley
- 2 readers on Citeulike
This Altmetric score means that the article is:
- in the 99th percentile (ranked 1,874th) of the 238,172 tracked articles of a similar age in all journals
- in the 95th percentile (ranked 37th) of the 768 tracked articles of a similar age in Nature Communications
Mentions in news, blogs & Google+
News articles (17)
- Computers trounce pathologists in predicting lung cancer type, severity, researchers find EurekAlert!
- Researchers’ computer program assesses lung cancer better than pathologists The Stanford Daily
- Computers better than doctors at assessing lung cancer samples: Study UPI.com
- Computers better than doctors at assessing lung cancer samples: Study Breitbart News Network
- Computers could be more accurate than pathologists in assessing lung cancer tissues, study shows The Medical News
- For Lung Cancer Diagnosis, Machine Learning can Prove More Accurate than Pathologists, Research Finds Healthcare Informatics
- Computers trounce pathologists in predicting lung cancer type and severity. ecancer ecancer
Scientific blogs (5)
- Predicting lung cancer type and patient survival with computers Scope Blog
- Computers Could Overtake Humans At Assessing Lung Cancer Tissue Samples: Study Medical Daily
- Are Computers Better than Doctors at Detecting Lung Cancer? Natural Society
- Smart medicine is coming of age, but will doctors bite? New Scientist - Astrobiology
Google+ posts (1)
|Country||Tweets||% of Tweets|
|No location data||63||33.51%|
Explanation of terms and methodology
Web of Science, CrossRef, Scopus, WebTrends, and Altmetric
Single number count for article citations from each service's database (may vary by service). The citations counts are reliant on the availability of the individual APIs from Web of Science, CrossRef, and Scopus. These counts are updated daily once they become available. Once a citation count is available, the list of articles citing this one is accessible by clicking on the circle for that citation source.
News, blogs and Google+ posts
The number of times an article has been cited by individual mainstream news sources, blog post, or member of Google+ along with a link to the original article or post. News articles, blog posts and Google+ posts do not always link to articles in a way that can be picked up by aggregators used by Altmetric, so the listed links are not necessarily a reflection of the entire scope of media, blog or Google+ interest. Further, the list of blogs and news sources covered is manually curated by Altmetric and thus is subject to their discretion for inclusion as a scientific blog or media source. The news, blog, and Google+ posts are provided by Altmetric and are updated hourly.
Altmetric calculates a score based on the online attention an article receives. Each coloured thread in the circle represents a different type of online attention and the number in the centre is the Altmetric score. The score is calculated based on two main sources of online attention: social media and mainstream news media. Altmetric also tracks usage in online reference managers such as Mendeley and CiteULike, but these do not contribute to the score. Older articles will typically score higher because they have had more time to get noticed. To account for this, Altmetric has included the context data for articles of a "similar age" (published within 6 weeks of either side of the publication date of this article).
For a more detailed description of Altmetric, the Altmetric score, and sources used, please see Altmetric's information page.
Provides the number of tweets broken down by country of origin for the Twitter account. The geographic breakdown for the twitter sources is provided by Altmetric and is updated hourly.