ArticleScientific reports2018
An Expert Diagnostic System to Automatically Identify Asthma and Chronic Obstructive Pulmonary Disease in Clinical Settings.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Classification of pulmonary diseases using machine learning and deep learning models on GLI-2012 standardized spirometry features.BMC medical informatics and decision making · 2026Article
- A baseline study of interpretable machine learning using GC-MS breath VOCs for classifying asthma, bronchiectasis, and COPD.Scientific reports · 2025Article
- Artificial Intelligence Applications in Chronic Obstructive Pulmonary Disease: A Global Scoping Review of Diagnostic, Symptom-Based, and Outcome Prediction Approaches.Biomedicines · 2025Review
- Vowel segmentation impact on machine learning classification for chronic obstructive pulmonary disease.Scientific reports · 2025Observational
- A chatbot based question and answer system for the auxiliary diagnosis of chronic diseases based on large language model.Scientific reports · 2024Article
- Integrating Artificial Intelligence in the Diagnosis of COPD Globally: A Way Forward.Chronic obstructive pulmonary diseases (Miami, Fla.) · 2024Article
- Predicting the Level of Respiratory Support in COVID-19 Patients Using Machine Learning.Bioengineering (Basel, Switzerland) · 2022Article
- Artificial intelligence to differentiate asthma from COPD in medico-administrative databases.BMC pulmonary medicine · 2022Article
- Prioritization of healthcare systems during pandemics using Cronbach's measure based fuzzy WASPAS approach.Annals of operations research · 2022Article
- A Hybrid Model to Classify Patients with Chronic Obstructive Respiratory Diseases.Journal of medical systems · 2021Article
- Deep learning based respiratory sound analysis for detection of chronic obstructive pulmonary disease.PeerJ. Computer science · 2021Article
- Neural Network-Based Clinical Prediction System for Identifying the Clinical Effects of Saffron (Crocus sativus L) Supplement Therapy on Allergic Asthma: Model Evaluation Study.JMIR medical informatics · 2020Article
- Artificial neural network identifies nonsteroidal anti-inflammatory drugs exacerbated respiratory disease (N-ERD) cohort.Allergy · 2020Article
- Personalized medicine for patients with COPD: where are we?International journal of chronic obstructive pulmonary disease · 2019Review
- Acoustic Methods for Pulmonary Diagnosis.IEEE reviews in biomedical engineering · 2019Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Respiratory diseases such as asthma and chronic obstructive pulmonary disease (COPD), are affecting a huge percentage of the world's population with mortality rates exceeding those of lung cancer and breast cancer combined. The major challenge is the number of patients who are incorrectly diagnosed. To address this, we developed an expert diagnostic system that can differentiate among patients with asthma, COPD or a normal lung function based on measurements of lung function and information about patient's symptoms. To develop accurate classification algorithms, data from 3657 patients were used and then independently verified using data from 1650 patients collected over a period of two years. Our results demonstrate that the expert diagnostic system can correctly identify patients with asthma and COPD with sensitivity of 96.45% and specificity of 98.71%. Additionally, 98.71% of the patients with a normal lung function were correctly classified, which contributed to a 49.23% decrease in demand for conducting additional tests, therefore decreasing financial cost.
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