An Intelligent Sensor Based Decision Support System for Diagnosing Pulmonary Ailment through Standardized Chest X-ray Scans
Academics and the health community are paying much attention to developing smart remote patient monitoring, sensors, and healthcare technology. For the analysis of medical scans, various studies integrate sophisticated deep learning strategies. A smart monitoring system is needed as a proactive diag...
| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/19/7474 |
| _version_ | 1797476868275830784 |
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| author | Shivani Batra Harsh Sharma Wadii Boulila Vaishali Arya Prakash Srivastava Mohammad Zubair Khan Moez Krichen |
| author_facet | Shivani Batra Harsh Sharma Wadii Boulila Vaishali Arya Prakash Srivastava Mohammad Zubair Khan Moez Krichen |
| author_sort | Shivani Batra |
| collection | DOAJ |
| description | Academics and the health community are paying much attention to developing smart remote patient monitoring, sensors, and healthcare technology. For the analysis of medical scans, various studies integrate sophisticated deep learning strategies. A smart monitoring system is needed as a proactive diagnostic solution that may be employed in an epidemiological scenario such as COVID-19. Consequently, this work offers an intelligent medicare system that is an IoT-empowered, deep learning-based decision support system (DSS) for the automated detection and categorization of infectious diseases (COVID-19 and pneumothorax). The proposed DSS system was evaluated using three independent standard-based chest X-ray scans. The suggested DSS predictor has been used to identify and classify areas on whole X-ray scans with abnormalities thought to be attributable to COVID-19, reaching an identification and classification accuracy rate of 89.58% for normal images and 89.13% for COVID-19 and pneumothorax. With the suggested DSS system, a judgment depending on individual chest X-ray scans may be made in approximately 0.01 s. As a result, the DSS system described in this study can forecast at a pace of 95 frames per second (FPS) for both models, which is near to real-time. |
| first_indexed | 2024-03-09T21:09:52Z |
| format | Article |
| id | doaj.art-20ef852cdf534f25b1653fd760d04995 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T21:09:52Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-20ef852cdf534f25b1653fd760d049952023-11-23T21:49:46ZengMDPI AGSensors1424-82202022-10-012219747410.3390/s22197474An Intelligent Sensor Based Decision Support System for Diagnosing Pulmonary Ailment through Standardized Chest X-ray ScansShivani Batra0Harsh Sharma1Wadii Boulila2Vaishali Arya3Prakash Srivastava4Mohammad Zubair Khan5Moez Krichen6Department of Computer Science and Engineering, KIET Group of Institutions, Delhi-NCR, Ghaziabad 201206, IndiaDepartment of Computer Science and Engineering, KIET Group of Institutions, Delhi-NCR, Ghaziabad 201206, IndiaRobotics and Internet-of-Things Laboratory, Prince Sultan University, Riyadh 12435, Saudi ArabiaSchool of Engineering, GD Goenka University, Gurugram 122103, IndiaDepartment of Computer Science and Engineering, Graphic Era (Deemed to Be University), Dehradun 248002, IndiaDepartment of Computer Science and Information, Taibah University, Medina 42353, Saudi ArabiaFaculty of Computer Science & IT, Al Baha University, Al Baha 65779, Saudi ArabiaAcademics and the health community are paying much attention to developing smart remote patient monitoring, sensors, and healthcare technology. For the analysis of medical scans, various studies integrate sophisticated deep learning strategies. A smart monitoring system is needed as a proactive diagnostic solution that may be employed in an epidemiological scenario such as COVID-19. Consequently, this work offers an intelligent medicare system that is an IoT-empowered, deep learning-based decision support system (DSS) for the automated detection and categorization of infectious diseases (COVID-19 and pneumothorax). The proposed DSS system was evaluated using three independent standard-based chest X-ray scans. The suggested DSS predictor has been used to identify and classify areas on whole X-ray scans with abnormalities thought to be attributable to COVID-19, reaching an identification and classification accuracy rate of 89.58% for normal images and 89.13% for COVID-19 and pneumothorax. With the suggested DSS system, a judgment depending on individual chest X-ray scans may be made in approximately 0.01 s. As a result, the DSS system described in this study can forecast at a pace of 95 frames per second (FPS) for both models, which is near to real-time.https://www.mdpi.com/1424-8220/22/19/7474chest X-ray scansCOVID-19decision support systemdeep leaningpneumothorax |
| spellingShingle | Shivani Batra Harsh Sharma Wadii Boulila Vaishali Arya Prakash Srivastava Mohammad Zubair Khan Moez Krichen An Intelligent Sensor Based Decision Support System for Diagnosing Pulmonary Ailment through Standardized Chest X-ray Scans Sensors chest X-ray scans COVID-19 decision support system deep leaning pneumothorax |
| title | An Intelligent Sensor Based Decision Support System for Diagnosing Pulmonary Ailment through Standardized Chest X-ray Scans |
| title_full | An Intelligent Sensor Based Decision Support System for Diagnosing Pulmonary Ailment through Standardized Chest X-ray Scans |
| title_fullStr | An Intelligent Sensor Based Decision Support System for Diagnosing Pulmonary Ailment through Standardized Chest X-ray Scans |
| title_full_unstemmed | An Intelligent Sensor Based Decision Support System for Diagnosing Pulmonary Ailment through Standardized Chest X-ray Scans |
| title_short | An Intelligent Sensor Based Decision Support System for Diagnosing Pulmonary Ailment through Standardized Chest X-ray Scans |
| title_sort | intelligent sensor based decision support system for diagnosing pulmonary ailment through standardized chest x ray scans |
| topic | chest X-ray scans COVID-19 decision support system deep leaning pneumothorax |
| url | https://www.mdpi.com/1424-8220/22/19/7474 |
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