| Title |
Predicting Nanoparticle Delivery to Tumors Using Machine Learning and Artificial Intelligence Approaches
|
|---|---|
| Published in |
International Journal of Nanomedicine, March 2022
|
| DOI | 10.2147/ijn.s344208 |
| Pubmed ID | |
| Authors |
Zhoumeng Lin, Wei-Chun Chou, Yi-Hsien Cheng, Chunla He, Nancy A Monteiro-Riviere, Jim E Riviere |
X Demographics
The data shown below were collected from the profiles of 30 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 2 | 7% |
| Spain | 2 | 7% |
| United States | 2 | 7% |
| Botswana | 1 | 3% |
| Austria | 1 | 3% |
| Switzerland | 1 | 3% |
| France | 1 | 3% |
| Egypt | 1 | 3% |
| Colombia | 1 | 3% |
| Other | 2 | 7% |
| Unknown | 16 | 53% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 25 | 83% |
| Science communicators (journalists, bloggers, editors) | 3 | 10% |
| Scientists | 1 | 3% |
| Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Mendeley readers
The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 57 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 12% |
| Professor | 3 | 5% |
| Student > Bachelor | 3 | 5% |
| Lecturer | 3 | 5% |
| Researcher | 3 | 5% |
| Other | 5 | 9% |
| Unknown | 33 | 58% |
| Readers by discipline | Count | As % |
|---|---|---|
| Pharmacology, Toxicology and Pharmaceutical Science | 6 | 11% |
| Biochemistry, Genetics and Molecular Biology | 4 | 7% |
| Chemical Engineering | 2 | 4% |
| Environmental Science | 2 | 4% |
| Medicine and Dentistry | 2 | 4% |
| Other | 8 | 14% |
| Unknown | 33 | 58% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 23 June 2022.
All research outputs
#2,598,421
of 25,392,582 outputs
Outputs from International Journal of Nanomedicine
#108
of 4,122 outputs
Outputs of similar age
#61,339
of 449,877 outputs
Outputs of similar age from International Journal of Nanomedicine
#2
of 42 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,122 research outputs from this source. They receive a mean Attention Score of 4.7. 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 449,877 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 42 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.