Name
Abstract | ||
|---|---|---|
Prescription medicine for asthma at primary stages is based on asthma severity level. Despite major progress in discovering various variables affecting asthma severity levels, disregarding some of these variables by physicians, variables' inherent uncertainty, and assigning patients to limited categories of decision making are the major causes of underestimating asthma severity, and as a result low quality of life in asthmatic patients. In this paper, we provide a solution of intelligence fuzzy system for this problem. Inputs of this system are organized in five modules of respiratory symptoms, bronchial obstruction, asthma instability, quality of life, and asthma severity. Output of this system is degree of asthma severity in score (0-10). Evaluating performance of this system by 28 asthmatic patients reinforces that the system's results not only correspond with evaluations of physicians, but represent the slight differences of asthmatic patients placed in specific category introduced by guidelines. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/s10916-010-9631-8 | J. Medical Systems |
Keywords | Field | DocType |
assessment severity,asthma severity,asthma instability,fuzzy rule-based expert system,assigning patient,intelligence fuzzy system,major progress,asthmatic patient,asthma severity level,result low quality,asthma severity.assessment.fuzzy. expert system,major cause,underestimating asthma severity,assessment,expert system,fuzzy | Data mining,Asthma,Quality of life,Physical therapy,Expert system,Intensive care medicine,Bronchial obstruction,Asthma severity,Medicine,Medical prescription,Fuzzy rule | Journal |
Volume | Issue | ISSN |
36 | 3 | 0148-5598 |
Citations | PageRank | References |
3 | 0.45 | 6 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maryam Zolnoori | 1 | 14 | 6.29 |
| Mohammad Hossein Fazel Zarandi | 2 | 189 | 19.38 |
| Mostafa Moin | 3 | 28 | 3.02 |
| Shahram Teimorian | 4 | 3 | 0.45 |