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Attention Score in Context
Chapter title |
Data Mining and Machine Learning Methods for Dementia Research
|
---|---|
Chapter number | 25 |
Book title |
Biomarkers for Alzheimer’s Disease Drug Development
|
Published in |
Methods in molecular biology, January 2018
|
DOI | 10.1007/978-1-4939-7704-8_25 |
Pubmed ID | |
Book ISBNs |
978-1-4939-7703-1, 978-1-4939-7704-8
|
Authors |
Rui Li |
Abstract |
Patient data in clinical research often includes large amounts of structured information, such as neuroimaging data, neuropsychological test results, and demographic variables. Given the various sources of information, we can develop computerized methods that can be a great help to clinicians to discover hidden patterns in the data. The computerized methods often employ data mining and machine learning algorithms, lending themselves as the computer-aided diagnosis (CAD) tool that assists clinicians in making diagnostic decisions. In this chapter, we review state-of-the-art methods used in dementia research, and briefly introduce some recently proposed algorithms subsequently. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 18 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 18 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Bachelor | 3 | 17% |
Researcher | 3 | 17% |
Other | 2 | 11% |
Professor | 1 | 6% |
Unspecified | 1 | 6% |
Other | 2 | 11% |
Unknown | 6 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 4 | 22% |
Computer Science | 3 | 17% |
Pharmacology, Toxicology and Pharmaceutical Science | 2 | 11% |
Unspecified | 1 | 6% |
Social Sciences | 1 | 6% |
Other | 1 | 6% |
Unknown | 6 | 33% |
Attention Score in Context
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 09 March 2018.
All research outputs
#18,590,133
of 23,026,672 outputs
Outputs from Methods in molecular biology
#7,971
of 13,170 outputs
Outputs of similar age
#330,575
of 442,370 outputs
Outputs of similar age from Methods in molecular biology
#950
of 1,499 outputs
Altmetric has tracked 23,026,672 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,170 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 24th percentile – i.e., 24% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.