Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model
Abdominal aortic aneurysm (AAA) is among the most widespread and dangerous diseases that may cause death. Recently, Endovascular Aneurysm Repair outperformed open aortic surgery, since it is a safe and reliable technique where a stent graft system is placed within the aortic aneurysm. It was aimed t...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9723037/ |
| _version_ | 1818442228663582720 |
|---|---|
| author | Rania E. Hammam Ahmed A. A. Solyman Mohammed H. Alsharif Peerapong Uthansakul Mohanad A. Deif |
| author_facet | Rania E. Hammam Ahmed A. A. Solyman Mohammed H. Alsharif Peerapong Uthansakul Mohanad A. Deif |
| author_sort | Rania E. Hammam |
| collection | DOAJ |
| description | Abdominal aortic aneurysm (AAA) is among the most widespread and dangerous diseases that may cause death. Recently, Endovascular Aneurysm Repair outperformed open aortic surgery, since it is a safe and reliable technique where a stent graft system is placed within the aortic aneurysm. It was aimed to design an Mg biodegradable alloy with bio-friendly alloying elements that enhance the corrosion resistance and mechanical properties of the alloy for the design of stents for Abdominal Aortic Aneurysm (AAA) repair. Adaptive Neuro-Fuzzy Inference System (ANFIS) was proposed for the design of the Mg alloy and compared to other traditional machine learning regression models (Multiple Linear Regression (MLR) and Gradient Boosting (GB). The dataset utilized in this work consisted of 600 samples of Mg alloys that were collected from the mat web database and additional papers from Google Scholar. The results revealed the superior prediction capability of the ANFIS model since it attained maximum <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> scores of 0.926, 0.958, and 0.988 for the prediction of UTS, YS, and Ductility respectively. Furthermore, the ANFIS model was capable of designing an Mg biodegradable alloy having a UTS, YS, and Ductility of 346.148 Mpa, 230.8 Mpa, and 15.4% respectively which are excellent mechanical properties satisfying vascular stents requirements The ANFIS model can be further applied to speed up the design of other alloys in the future for various medical applications, reducing the time, cost, and effort of large searching space. |
| first_indexed | 2024-12-14T18:40:49Z |
| format | Article |
| id | doaj.art-337adec01ed44c7a9253a7fa6913b691 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T18:40:49Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-337adec01ed44c7a9253a7fa6913b6912022-12-21T22:51:30ZengIEEEIEEE Access2169-35362022-01-0110285792858910.1109/ACCESS.2022.31556459723037Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression ModelRania E. Hammam0https://orcid.org/0000-0002-1460-3115Ahmed A. A. Solyman1https://orcid.org/0000-0002-2881-8635Mohammed H. Alsharif2https://orcid.org/0000-0001-8579-5444Peerapong Uthansakul3https://orcid.org/0000-0002-7108-9263Mohanad A. Deif4https://orcid.org/0000-0002-4388-1480Department of Bioelectronics, Modern University for Technology & Information (MTI), Cairo, EgyptDepartment of Electrical and Electronics Engineering, Istanbul Gelisim University, Istanbul, Avcilar, TurkeyDepartment of Electrical Engineering, College of Electronics and Information Engineering, Sejong University, Seoul, Gwangjin-gu, South KoreaSchool of Telecommunication Engineering, Suranaree University of Technology, Nakhon Ratchasima, ThailandDepartment of Bioelectronics, Modern University for Technology & Information (MTI), Cairo, EgyptAbdominal aortic aneurysm (AAA) is among the most widespread and dangerous diseases that may cause death. Recently, Endovascular Aneurysm Repair outperformed open aortic surgery, since it is a safe and reliable technique where a stent graft system is placed within the aortic aneurysm. It was aimed to design an Mg biodegradable alloy with bio-friendly alloying elements that enhance the corrosion resistance and mechanical properties of the alloy for the design of stents for Abdominal Aortic Aneurysm (AAA) repair. Adaptive Neuro-Fuzzy Inference System (ANFIS) was proposed for the design of the Mg alloy and compared to other traditional machine learning regression models (Multiple Linear Regression (MLR) and Gradient Boosting (GB). The dataset utilized in this work consisted of 600 samples of Mg alloys that were collected from the mat web database and additional papers from Google Scholar. The results revealed the superior prediction capability of the ANFIS model since it attained maximum <inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula> scores of 0.926, 0.958, and 0.988 for the prediction of UTS, YS, and Ductility respectively. Furthermore, the ANFIS model was capable of designing an Mg biodegradable alloy having a UTS, YS, and Ductility of 346.148 Mpa, 230.8 Mpa, and 15.4% respectively which are excellent mechanical properties satisfying vascular stents requirements The ANFIS model can be further applied to speed up the design of other alloys in the future for various medical applications, reducing the time, cost, and effort of large searching space.https://ieeexplore.ieee.org/document/9723037/Abdominal aortic aneurysmANFISbiodegradablegradient boostingMg alloy |
| spellingShingle | Rania E. Hammam Ahmed A. A. Solyman Mohammed H. Alsharif Peerapong Uthansakul Mohanad A. Deif Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model IEEE Access Abdominal aortic aneurysm ANFIS biodegradable gradient boosting Mg alloy |
| title | Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model |
| title_full | Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model |
| title_fullStr | Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model |
| title_full_unstemmed | Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model |
| title_short | Design of Biodegradable Mg Alloy for Abdominal Aortic Aneurysm Repair (AAAR) Using ANFIS Regression Model |
| title_sort | design of biodegradable mg alloy for abdominal aortic aneurysm repair aaar using anfis regression model |
| topic | Abdominal aortic aneurysm ANFIS biodegradable gradient boosting Mg alloy |
| url | https://ieeexplore.ieee.org/document/9723037/ |
| work_keys_str_mv | AT raniaehammam designofbiodegradablemgalloyforabdominalaorticaneurysmrepairaaarusinganfisregressionmodel AT ahmedaasolyman designofbiodegradablemgalloyforabdominalaorticaneurysmrepairaaarusinganfisregressionmodel AT mohammedhalsharif designofbiodegradablemgalloyforabdominalaorticaneurysmrepairaaarusinganfisregressionmodel AT peeraponguthansakul designofbiodegradablemgalloyforabdominalaorticaneurysmrepairaaarusinganfisregressionmodel AT mohanadadeif designofbiodegradablemgalloyforabdominalaorticaneurysmrepairaaarusinganfisregressionmodel |