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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
|
|---|---|
| Published in |
Nature Communications, August 2016
|
| DOI | 10.1038/ncomms12474 |
| Pubmed ID | |
| Authors |
Kun-Hsing Yu, Ce Zhang, Gerald J. Berry, Russ B. Altman, Christopher Ré, Daniel L. Rubin, Michael Snyder |
| Abstract |
Lung cancer is the most prevalent cancer worldwide, and histopathological assessment is indispensable for its diagnosis. However, human evaluation of pathology slides cannot accurately predict patients' prognoses. In this study, we obtain 2,186 haematoxylin and eosin stained histopathology whole-slide images of lung adenocarcinoma and squamous cell carcinoma patients from The Cancer Genome Atlas (TCGA), and 294 additional images from Stanford Tissue Microarray (TMA) Database. We extract 9,879 quantitative image features and use regularized machine-learning methods to select the top features and to distinguish shorter-term survivors from longer-term survivors with stage I adenocarcinoma (P<0.003) or squamous cell carcinoma (P=0.023) in the TCGA data set. We validate the survival prediction framework with the TMA cohort (P<0.036 for both tumour types). Our results suggest that automatically derived image features can predict the prognosis of lung cancer patients and thereby contribute to precision oncology. Our methods are extensible to histopathology images of other organs. |
X Demographics
The data shown below were collected from the profiles of 183 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 67 | 37% |
| United Kingdom | 11 | 6% |
| France | 6 | 3% |
| India | 6 | 3% |
| Canada | 4 | 2% |
| Mexico | 3 | 2% |
| Spain | 3 | 2% |
| Belgium | 2 | 1% |
| Brazil | 2 | 1% |
| Other | 21 | 11% |
| Unknown | 58 | 32% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 113 | 62% |
| Scientists | 59 | 32% |
| Practitioners (doctors, other healthcare professionals) | 7 | 4% |
| Science communicators (journalists, bloggers, editors) | 4 | 2% |
Mendeley readers
The data shown below were compiled from readership statistics for 819 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 4 | <1% |
| United Kingdom | 3 | <1% |
| France | 2 | <1% |
| Germany | 2 | <1% |
| Sweden | 2 | <1% |
| Switzerland | 2 | <1% |
| Turkey | 1 | <1% |
| Brazil | 1 | <1% |
| Spain | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 800 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 146 | 18% |
| Researcher | 130 | 16% |
| Student > Master | 97 | 12% |
| Student > Bachelor | 57 | 7% |
| Other | 46 | 6% |
| Other | 144 | 18% |
| Unknown | 199 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 152 | 19% |
| Computer Science | 137 | 17% |
| Biochemistry, Genetics and Molecular Biology | 72 | 9% |
| Engineering | 72 | 9% |
| Agricultural and Biological Sciences | 61 | 7% |
| Other | 95 | 12% |
| Unknown | 230 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 292. 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 04 May 2023.
All research outputs
#122,164
of 25,775,807 outputs
Outputs from Nature Communications
#1,754
of 58,407 outputs
Outputs of similar age
#2,376
of 338,943 outputs
Outputs of similar age from Nature Communications
#38
of 801 outputs
Altmetric has tracked 25,775,807 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 58,407 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.4. 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 338,943 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 99% of its contemporaries.
We're also able to compare this research output to 801 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 95% of its contemporaries.