Accepted for/Published in: JMIR Medical Informatics
Date Submitted: Dec 21, 2019
Date Accepted: Feb 26, 2020
A Clinical Predictor System for Detecting the Improvement Level of Allergic Asthma Patients with Saffron Supplement Therapy Running title: Predicting System for Asthma Improvement Level
ABSTRACT
Background:
Asthma is commonly associated with chronic airway inflammation and it is the underlying cause of over a million deaths each year. Statistical reports show that traditional medicine using saffron has anti-inflammatory effects and may be beneficial to asthma. Artificial neural network (ANN) models can offer significant improvement over traditional statistical reports.
Objective:
The objective of this study was to provide a clinical predictor system (CPS) to detect potential effects of saffron supplement on allergic asthma patients using an ANN.
Methods:
A genetic-neural network (GNN) system was designed that utilized clinical, immunologic, hematologic, and demographic information of asthma patients to detect the level of effectiveness of saffron. This model aims to fulfill two main purposes: estimating and predicting the possible effects level of saffron supplement on every risk factors and predicting the level of improvement in patients. For improving the prediction performance a genetic algorithm (GA) model was used to extract the input features of the predictor system. Moreover, an optimization model was developed to address applicable architecture of ANN that classifies the asthma patients with saffron supplement therapy.
Results:
The experimental results showed that the overall performance of the proposed system with the best precision was more than 99% for training and testing experiments. Moreover, the proposed GNN system predicted the level of effects with approximate accuracy rates for anti-HSP (96.5%), HS-CRP (98.9%), FEV1 (98.1%), FVC (97.5%), FEV1/FVC ratio (97%) and FEF25-75 (96.7%) for the testing dataset.
Conclusions:
The proposed system was effective in estimating the potential effects of saffron supplement on the allergic asthma patients. Most importantly, this study contributes to clinical knowledge by helping clinicians to early identify which of the asthma clinical factors will continue to improve during the treatment and draw a plan in order to change the natural course of the disease.
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Copyright
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