| Paper Abstract and Keywords |
| Presentation |
2023-02-16 14:30
Predicting Temperature Rise Using Machine Learning in Microwave Heating
Tohgo Hosoda, Aditya Rakhmadi, Kazuyuki Saito (Chiba Univ.) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
In recent years, research on machine learning has been active, and use of technology been increasing in various fields where computers are employed to learn past data and predict response values. We have been studying the possibility of applying machine learning to the medical field. In Japan, the number of hypertensive patients is increasing due to the westernization of diets. Therefore, there is a need to establish a treatment method for hypertension. Renal denervation (RDN) is one of the treatments for hypertension and involves ablating the nerves outside the renal artery. However, there is a problem that it is impossible to know whether the target area is ablated during renal denervation. Because there is no established method to confirm the outside temperature of the renal artery in real time. In order to solve this problem, we introduced machine learning for nerve ablation using microwave energy. In the technique, the temperature of the nerve outside the renal artery is predicted from the temperature inside the renal artery, which can be observed. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Machine learning / hypertension / renal denervation / microwave / temperature analysis / XGBoost / / |
| Reference Info. |
ITE Tech. Rep., vol. 47, no. 5, BCT2023-18, pp. 1-4, Feb. 2023. |
| Paper # |
BCT2023-18 |
| Date of Issue |
2023-02-09 (BCT) |
| ISSN |
Print edition: ISSN 1342-6893 Online edition: ISSN 2424-1970 |
| Download PDF |
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| Conference Information |
| Committee |
BCT IEEE-BT |
| Conference Date |
2023-02-16 - 2023-02-17 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Osaka Museum of History |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
BCT |
| Conference Code |
2023-02-BCT-BT |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Predicting Temperature Rise Using Machine Learning in Microwave Heating |
| Sub Title (in English) |
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| Keyword(1) |
Machine learning |
| Keyword(2) |
hypertension |
| Keyword(3) |
renal denervation |
| Keyword(4) |
microwave |
| Keyword(5) |
temperature analysis |
| Keyword(6) |
XGBoost |
| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Tohgo Hosoda |
| 1st Author's Affiliation |
Chiba University (Chiba Univ.) |
| 2nd Author's Name |
Aditya Rakhmadi |
| 2nd Author's Affiliation |
Chiba University (Chiba Univ.) |
| 3rd Author's Name |
Kazuyuki Saito |
| 3rd Author's Affiliation |
Chiba University (Chiba Univ.) |
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| Speaker |
Author-1 |
| Date Time |
2023-02-16 14:30:00 |
| Presentation Time |
20 minutes |
| Registration for |
BCT |
| Paper # |
BCT2023-18 |
| Volume (vol) |
vol.47 |
| Number (no) |
no.5 |
| Page |
pp.1-4 |
| #Pages |
4 |
| Date of Issue |
2023-02-09 (BCT) |
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