| Title |
AAPM task group report 273: Recommendations on best practices for AI and machine learning for computer‐aided diagnosis in medical imaging
|
|---|---|
| Published in |
Medical Physics, January 2023
|
| DOI | 10.1002/mp.16188 |
| Pubmed ID | |
| Authors |
Lubomir Hadjiiski, Kenny Cha, Heang‐Ping Chan, Karen Drukker, Lia Morra, Janne J. Näppi, Berkman Sahiner, Hiroyuki Yoshida, Quan Chen, Thomas M. Deserno, Hayit Greenspan, Henkjan Huisman, Zhimin Huo, Richard Mazurchuk, Nicholas Petrick, Daniele Regge, Ravi Samala, Ronald M. Summers, Kenji Suzuki, Georgia Tourassi, Daniel Vergara, Samuel G. Armato |
X Demographics
The data shown below were collected from the profiles of 6 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 | 1 | 17% |
| Russia | 1 | 17% |
| Netherlands | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Practitioners (doctors, other healthcare professionals) | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 65 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 8 | 12% |
| Unspecified | 5 | 8% |
| Student > Ph. D. Student | 5 | 8% |
| Other | 5 | 8% |
| Student > Bachelor | 5 | 8% |
| Other | 11 | 17% |
| Unknown | 26 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 15% |
| Engineering | 6 | 9% |
| Computer Science | 4 | 6% |
| Unspecified | 4 | 6% |
| Nursing and Health Professions | 4 | 6% |
| Other | 10 | 15% |
| Unknown | 27 | 42% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 March 2023.
All research outputs
#7,116,227
of 23,891,012 outputs
Outputs from Medical Physics
#1,737
of 7,869 outputs
Outputs of similar age
#125,798
of 447,382 outputs
Outputs of similar age from Medical Physics
#12
of 104 outputs
Altmetric has tracked 23,891,012 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 7,869 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 77% 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 447,382 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 104 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.