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Mendeley readers
Attention Score in Context
| Title |
Artificial intelligence in healthcare: past, present and future
|
|---|---|
| Published in |
Stroke and Vascular Neurology, June 2017
|
| DOI | 10.1136/svn-2017-000101 |
| Pubmed ID | |
| Authors |
Fei Jiang, Yong Jiang, Hui Zhi, Yi Dong, Hao Li, Sufeng Ma, Yilong Wang, Qiang Dong, Haipeng Shen, Yongjun Wang |
| Abstract |
Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI. |
X Demographics
The data shown below were collected from the profiles of 77 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 | 12 | 16% |
| India | 7 | 9% |
| Spain | 5 | 6% |
| United Kingdom | 5 | 6% |
| Germany | 4 | 5% |
| Austria | 3 | 4% |
| Belgium | 2 | 3% |
| Saudi Arabia | 2 | 3% |
| Namibia | 1 | 1% |
| Other | 8 | 10% |
| Unknown | 28 | 36% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 62 | 81% |
| Scientists | 6 | 8% |
| Practitioners (doctors, other healthcare professionals) | 5 | 6% |
| Science communicators (journalists, bloggers, editors) | 4 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 4,560 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4560 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 598 | 13% |
| Student > Bachelor | 549 | 12% |
| Student > Ph. D. Student | 449 | 10% |
| Researcher | 338 | 7% |
| Student > Doctoral Student | 172 | 4% |
| Other | 646 | 14% |
| Unknown | 1808 | 40% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 615 | 13% |
| Medicine and Dentistry | 475 | 10% |
| Engineering | 382 | 8% |
| Business, Management and Accounting | 205 | 4% |
| Biochemistry, Genetics and Molecular Biology | 131 | 3% |
| Other | 789 | 17% |
| Unknown | 1963 | 43% |
Attention Score in Context
This research output has an Altmetric Attention Score of 221. 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 12 January 2024.
All research outputs
#176,897
of 25,698,912 outputs
Outputs from Stroke and Vascular Neurology
#4
of 429 outputs
Outputs of similar age
#3,719
of 331,844 outputs
Outputs of similar age from Stroke and Vascular Neurology
#1
of 10 outputs
Altmetric has tracked 25,698,912 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 429 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has done particularly well, scoring higher than 99% 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 331,844 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 98% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them