A Huge Innovation in Diagnosis of Obstructive Sleep Apnea Syndrome: With an Artificial Intelligence-Based Algorithm, Obstructive Sleep Apnea Syndrome Can Now Be Diagnosed With Pulmonary Function Test
Obstructive sleep apnea syndrome (OSAS) is a life-threatening disease characterized by upper airway narrowing or obstruction. The diagnostic process is difficult, costly, and time-consuming. Many individuals with OSAS do not apply for a diagnosis or are unaware of their disease. This study aimed to...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10845768/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832583999949635584 |
|---|---|
| author | Seval Bulut Eris Mehmet Recep Bozkurt Omer Eris Cahit Bilgin |
| author_facet | Seval Bulut Eris Mehmet Recep Bozkurt Omer Eris Cahit Bilgin |
| author_sort | Seval Bulut Eris |
| collection | DOAJ |
| description | Obstructive sleep apnea syndrome (OSAS) is a life-threatening disease characterized by upper airway narrowing or obstruction. The diagnostic process is difficult, costly, and time-consuming. Many individuals with OSAS do not apply for a diagnosis or are unaware of their disease. This study aimed to develop a practical, fast, and reliable diagnostic system for early diagnosis and treatment of OSAS. For the first time, features were extracted from flow-volume curves obtained using a Pulmonary Function Test (PFT), and an Artificial Intelligence (AI)-based algorithm was developed to diagnose OSAS. Spearman correlation coefficients determined the degree of influence of the features in determining OSAS. Several models were created using different features and AI methods according to their effect levels. The models obtained by hyperparameter optimization and cross-validation were tested with unseen data, and their performance was evaluated using seven different criteria. Using only five features extracted from the flow-volume curve (TLC/PIF, PIF/PEF, TLC/FIF50, TLC/FIF25, and FIF25/FEF25), OSAS was diagnosed with 97.1% accuracy using the Neural Network (NN) algorithm. The results showed that OSAS can be diagnosed quickly and reliably using PFT available at every hospital. The features extracted from the flow-volume curve could be used as biomarkers for diagnosing OSAS. The proposed method can be adapted to PC-based spirometry devices without additional hardware developments. This is a significant innovation in both literature and practice. This method will enable early diagnosis for patients and many people unaware of their disease. This will shed light on several future studies. |
| format | Article |
| id | doaj-art-c30c085af3f24e9c8f60e0b395ff308e |
| institution | Kabale University |
| issn | 2169-3536 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj-art-c30c085af3f24e9c8f60e0b395ff308e2025-01-28T00:01:17ZengIEEEIEEE Access2169-35362025-01-0113153761538910.1109/ACCESS.2025.353150110845768A Huge Innovation in Diagnosis of Obstructive Sleep Apnea Syndrome: With an Artificial Intelligence-Based Algorithm, Obstructive Sleep Apnea Syndrome Can Now Be Diagnosed With Pulmonary Function TestSeval Bulut Eris0https://orcid.org/0000-0001-8681-1848Mehmet Recep Bozkurt1https://orcid.org/0000-0003-0673-4454Omer Eris2https://orcid.org/0000-0003-1687-5912Cahit Bilgin3Electrical and Electronics Engineering Department, Sakarya University, Sakarya, TürkiyeElectrical and Electronics Engineering Department, Sakarya University, Sakarya, TürkiyeElectrical and Electronics Engineering Department, Sakarya University, Sakarya, TürkiyeFaculty of Medicine, Sakarya University, Sakarya, TürkiyeObstructive sleep apnea syndrome (OSAS) is a life-threatening disease characterized by upper airway narrowing or obstruction. The diagnostic process is difficult, costly, and time-consuming. Many individuals with OSAS do not apply for a diagnosis or are unaware of their disease. This study aimed to develop a practical, fast, and reliable diagnostic system for early diagnosis and treatment of OSAS. For the first time, features were extracted from flow-volume curves obtained using a Pulmonary Function Test (PFT), and an Artificial Intelligence (AI)-based algorithm was developed to diagnose OSAS. Spearman correlation coefficients determined the degree of influence of the features in determining OSAS. Several models were created using different features and AI methods according to their effect levels. The models obtained by hyperparameter optimization and cross-validation were tested with unseen data, and their performance was evaluated using seven different criteria. Using only five features extracted from the flow-volume curve (TLC/PIF, PIF/PEF, TLC/FIF50, TLC/FIF25, and FIF25/FEF25), OSAS was diagnosed with 97.1% accuracy using the Neural Network (NN) algorithm. The results showed that OSAS can be diagnosed quickly and reliably using PFT available at every hospital. The features extracted from the flow-volume curve could be used as biomarkers for diagnosing OSAS. The proposed method can be adapted to PC-based spirometry devices without additional hardware developments. This is a significant innovation in both literature and practice. This method will enable early diagnosis for patients and many people unaware of their disease. This will shed light on several future studies.https://ieeexplore.ieee.org/document/10845768/Artificial intelligencebiomarkersfeature extractionflow-volume curveobstructive sleep apneapulmonary function test |
| spellingShingle | Seval Bulut Eris Mehmet Recep Bozkurt Omer Eris Cahit Bilgin A Huge Innovation in Diagnosis of Obstructive Sleep Apnea Syndrome: With an Artificial Intelligence-Based Algorithm, Obstructive Sleep Apnea Syndrome Can Now Be Diagnosed With Pulmonary Function Test IEEE Access Artificial intelligence biomarkers feature extraction flow-volume curve obstructive sleep apnea pulmonary function test |
| title | A Huge Innovation in Diagnosis of Obstructive Sleep Apnea Syndrome: With an Artificial Intelligence-Based Algorithm, Obstructive Sleep Apnea Syndrome Can Now Be Diagnosed With Pulmonary Function Test |
| title_full | A Huge Innovation in Diagnosis of Obstructive Sleep Apnea Syndrome: With an Artificial Intelligence-Based Algorithm, Obstructive Sleep Apnea Syndrome Can Now Be Diagnosed With Pulmonary Function Test |
| title_fullStr | A Huge Innovation in Diagnosis of Obstructive Sleep Apnea Syndrome: With an Artificial Intelligence-Based Algorithm, Obstructive Sleep Apnea Syndrome Can Now Be Diagnosed With Pulmonary Function Test |
| title_full_unstemmed | A Huge Innovation in Diagnosis of Obstructive Sleep Apnea Syndrome: With an Artificial Intelligence-Based Algorithm, Obstructive Sleep Apnea Syndrome Can Now Be Diagnosed With Pulmonary Function Test |
| title_short | A Huge Innovation in Diagnosis of Obstructive Sleep Apnea Syndrome: With an Artificial Intelligence-Based Algorithm, Obstructive Sleep Apnea Syndrome Can Now Be Diagnosed With Pulmonary Function Test |
| title_sort | huge innovation in diagnosis of obstructive sleep apnea syndrome with an artificial intelligence based algorithm obstructive sleep apnea syndrome can now be diagnosed with pulmonary function test |
| topic | Artificial intelligence biomarkers feature extraction flow-volume curve obstructive sleep apnea pulmonary function test |
| url | https://ieeexplore.ieee.org/document/10845768/ |
| work_keys_str_mv | AT sevalbuluteris ahugeinnovationindiagnosisofobstructivesleepapneasyndromewithanartificialintelligencebasedalgorithmobstructivesleepapneasyndromecannowbediagnosedwithpulmonaryfunctiontest AT mehmetrecepbozkurt ahugeinnovationindiagnosisofobstructivesleepapneasyndromewithanartificialintelligencebasedalgorithmobstructivesleepapneasyndromecannowbediagnosedwithpulmonaryfunctiontest AT omereris ahugeinnovationindiagnosisofobstructivesleepapneasyndromewithanartificialintelligencebasedalgorithmobstructivesleepapneasyndromecannowbediagnosedwithpulmonaryfunctiontest AT cahitbilgin ahugeinnovationindiagnosisofobstructivesleepapneasyndromewithanartificialintelligencebasedalgorithmobstructivesleepapneasyndromecannowbediagnosedwithpulmonaryfunctiontest AT sevalbuluteris hugeinnovationindiagnosisofobstructivesleepapneasyndromewithanartificialintelligencebasedalgorithmobstructivesleepapneasyndromecannowbediagnosedwithpulmonaryfunctiontest AT mehmetrecepbozkurt hugeinnovationindiagnosisofobstructivesleepapneasyndromewithanartificialintelligencebasedalgorithmobstructivesleepapneasyndromecannowbediagnosedwithpulmonaryfunctiontest AT omereris hugeinnovationindiagnosisofobstructivesleepapneasyndromewithanartificialintelligencebasedalgorithmobstructivesleepapneasyndromecannowbediagnosedwithpulmonaryfunctiontest AT cahitbilgin hugeinnovationindiagnosisofobstructivesleepapneasyndromewithanartificialintelligencebasedalgorithmobstructivesleepapneasyndromecannowbediagnosedwithpulmonaryfunctiontest |