| Presentation | 2018-12-15 Prediction of side effects by deep learning using drug side effect database (JADER) Hiroki Matsui, Sumio Matsuno, Ryo Onoda, Naoki Ohboshi, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Drug use Grasping the occurrence trend of adverse events as an application of safety information after marketing contributes to the early detection and adequate response of adverse events and is important in proper use of pharmaceutical products. Also, using these data, it is possible to grasp the tendency of adverse events to develop. Have great value in the decision of a doctor who chooses a medicine. Therefore, in this study, we predict adverse events that could occur by machine learning using medicine side effect database (JADER) published by Independent Administrative Agency Pharmaceuticals and Medical Devices Agency (PMDA) and analyzed the results. Predicting possible adverse events from these data as multi-class classification problems, we could predict with an average of about 81% recall. In addition, when we scrutinized the remaining 19% of unexpected results, there were many cases where many medications were administered, and the possibility that it was an unknown adverse event due to polypharmacy could be considered. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | JADER / Machine Learning / DNN / Side Effect |
| Paper # | NC2018-28 |
| Date of Issue | 2018-12-08 (NC) |
| Conference Information | |
| Committee | NC / MBE |
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| Conference Date | 2018/12/15(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Nagoya Institute of Technology |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Yutaka Hirata(Chubu Univ.) / Masaki Kyoso(TCU) |
| Vice Chair | Hayaru Shouno(UEC) / Taishin Nomura(Osaka Univ.) |
| Secretary | Hayaru Shouno(Nagoya Univ.) / Taishin Nomura(NAIST) |
| Assistant | Keiichiro Inagaki(Chubu Univ.) / Takashi Shinozaki(NICT) / Takumi Kobayashi(YNU) / Ｙａｓｕｙｕｋｉ Ｓｕｚｕｋｉ(Osaka Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Neurocomputing / Technical Committee on ME and Bio Cybernetics |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Prediction of side effects by deep learning using drug side effect database (JADER) |
| Sub Title (in English) | |
| Keyword(1) | JADER |
| Keyword(2) | Machine Learning |
| Keyword(3) | DNN |
| Keyword(4) | Side Effect |
| 1st Author's Name | Hiroki Matsui |
| 1st Author's Affiliation | Kindai University(Kindai Univ.) |
| 2nd Author's Name | Sumio Matsuno |
| 2nd Author's Affiliation | Kindai University(Kindai Univ.) |
| 3rd Author's Name | Ryo Onoda |
| 3rd Author's Affiliation | Kindai University(Kindai Univ.) |
| 4th Author's Name | Naoki Ohboshi |
| 4th Author's Affiliation | Kindai University(Kindai Univ.) |
| Date | 2018-12-15 |
| Paper # | NC2018-28 |
| Volume (vol) | vol.118 |
| Number (no) | NC-367 |
| Page | pp.pp.1-4(NC), |
| #Pages | 4 |
| Date of Issue | 2018-12-08 (NC) |