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Chronic obstructive lung disease “expert system”: validation of a predictive tool for assisting diagnosis

Overview of attention for article published in International Journal of Chronic Obstructive Pulmonary Disease, May 2018
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2 tweeters

Citations

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8 Mendeley
Title
Chronic obstructive lung disease “expert system”: validation of a predictive tool for assisting diagnosis
Published in
International Journal of Chronic Obstructive Pulmonary Disease, May 2018
DOI 10.2147/copd.s165533
Pubmed ID
Authors

Fulvio Braido, Pierachille Santus, Angelo Corsico, Fabiano Di Marco, Giovanni Melioli, Nicola Scichilone, Paolo Solidoro

Abstract

The purposes of this study were development and validation of an expert system (ES) aimed at supporting the diagnosis of chronic obstructive lung disease (COLD). A questionnaire and a WebFlex code were developed and validated in silico. An expert panel pilot validation on 60 cases and a clinical validation on 241 cases were performed. The developed questionnaire and code validated in silico resulted in a suitable tool to support the medical diagnosis. The clinical validation of the ES was performed in an academic setting that included six different reference centers for respiratory diseases. The results of the ES expressed as a score associated with the risk of suffering from COLD were matched and compared with the final clinical diagnoses. A set of 60 patients were evaluated by a pilot expert panel validation with the aim of calculating the sample size for the clinical validation study. The concordance analysis between these preliminary ES scores and diagnoses performed by the experts indicated that the accuracy was 94.7% when both experts and the system confirmed the COLD diagnosis and 86.3% when COLD was excluded. Based on these results, the sample size of the validation set was established in 240 patients. The clinical validation, performed on 241 patients, resulted in ES accuracy of 97.5%, with confirmed COLD diagnosis in 53.6% of the cases and excluded COLD diagnosis in 32% of the cases. In 11.2% of cases, a diagnosis of COLD was made by the experts, although the imaging results showed a potential concomitant disorder. The ES presented here (COLDES) is a safe and robust supporting tool for COLD diagnosis in primary care settings.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 25%
Student > Bachelor 2 25%
Student > Master 1 13%
Other 1 13%
Student > Doctoral Student 1 13%
Other 1 13%
Readers by discipline Count As %
Unspecified 3 38%
Medicine and Dentistry 2 25%
Nursing and Health Professions 1 13%
Pharmacology, Toxicology and Pharmaceutical Science 1 13%
Engineering 1 13%
Other 0 0%

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 28 May 2018.
All research outputs
#9,944,465
of 12,996,278 outputs
Outputs from International Journal of Chronic Obstructive Pulmonary Disease
#1,156
of 1,578 outputs
Outputs of similar age
#187,744
of 271,364 outputs
Outputs of similar age from International Journal of Chronic Obstructive Pulmonary Disease
#49
of 59 outputs
Altmetric has tracked 12,996,278 research outputs across all sources so far. This one is in the 20th percentile – i.e., 20% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,578 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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 271,364 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 59 others from the same source and published within six weeks on either side of this one. This one is in the 13th percentile – i.e., 13% of its contemporaries scored the same or lower than it.