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Mendeley readers
Attention Score in Context
| Title |
Automatic Diagnosis of Tuberculosis Disease Based on Plasmonic ELISA and Color-based Image Classification
|
|---|---|
| Published in |
Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society, July 2017
|
| DOI | 10.1109/embc.2017.8037859 |
| Pubmed ID | |
| Authors |
Kamal J. AbuHassan, Marzia H. Tania, Benjamin A. Evans, Nor A. Yusof, M. A. Hossain, Noremylia M. Bakhori, Norzila Kusnin, Umi Z.M. Azmi |
| Abstract |
Tuberculosis (TB) remains one of the most devastating infectious diseases and its treatment efficiency is majorly influenced by the stage at which infection with the TB bacterium is diagnosed. The available methods for TB diagnosis are either time consuming, costly or not efficient. This study employs a signal generation mechanism for biosensing, known as Plasmonic ELISA, and computational intelligence to facilitate automatic diagnosis of TB. Plasmonic ELISA enables the detection of a few molecules of analyte by the incorporation of smart nanomaterials for better sensitivity of the developed detection system. The computational system uses k-means clustering and thresholding for image segmentation. This paper presents the results of the classification performance of the Plasmonic ELISA imaging data by using various types of classifiers. The five-fold cross-validation results show high accuracy rate (>97%) in classifying TB images using the entire data set. Future work will focus on developing an intelligent mobile-enabled expert system to diagnose TB in real-time. The intelligent system will be clinically validated and tested in collaboration with healthcare providers in Malaysia. |
Mendeley readers
The data shown below were compiled from readership statistics for 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 28 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 7 | 25% |
| Lecturer | 3 | 11% |
| Student > Doctoral Student | 3 | 11% |
| Researcher | 3 | 11% |
| Student > Ph. D. Student | 3 | 11% |
| Other | 5 | 18% |
| Unknown | 4 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 18% |
| Engineering | 4 | 14% |
| Biochemistry, Genetics and Molecular Biology | 2 | 7% |
| Nursing and Health Professions | 2 | 7% |
| Medicine and Dentistry | 2 | 7% |
| Other | 7 | 25% |
| Unknown | 6 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 3. 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 03 March 2022.
All research outputs
#8,537,346
of 25,382,440 outputs
Outputs from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#847
of 4,376 outputs
Outputs of similar age
#126,415
of 326,871 outputs
Outputs of similar age from Conference proceedings Annual International Conference of the IEEE Engineering in Medicine and Biology Society
#38
of 239 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,376 research outputs from this source. They receive a mean Attention Score of 2.7. This one has gotten more attention than average, scoring higher than 57% 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 326,871 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 52% of its contemporaries.
We're also able to compare this research output to 239 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.