Predictive factors for the progression of primary small-bowel follicular lymphoma and disease surveillance evaluation using capsule endoscopy images based on AI system 1）Predictive factors for the progression of primary localized stage small-bowel follicular lymphoma 2）Disease surveillance evaluation of primary small-bowel follicular lymphoma using capsule endoscopy images based on a deep convolutional neural network
アクセス数 : 53 件
ダウンロード数 : 77 件
今月のアクセス数 : 4 件
今月のダウンロード数 : 8 件
この文献の参照には次のURLをご利用ください : https://ir.lib.hiroshima-u.ac.jp/00055546
| File | |
| File | |
| File | |
| File | |
| Title ( eng ) |
Predictive factors for the progression of primary small-bowel follicular lymphoma and disease surveillance evaluation using capsule endoscopy images based on AI system 1）Predictive factors for the progression of primary localized stage small-bowel follicular lymphoma 2）Disease surveillance evaluation of primary small-bowel follicular lymphoma using capsule endoscopy images based on a deep convolutional neural network
|
| Title ( jpn ) |
原発性小腸濾胞性リンパ腫の進行予測因子とAIシステムに基づくカプセル内視鏡画像を用いた病勢評価 1）原発性限局期小腸濾胞性リンパ腫の進行予測因子 2）深層畳み込みニューラルネットワークに基づくカプセル内視鏡画像を用いた原発性小腸濾胞性リンパ腫の病勢評価
|
| Creator |
Sumioka Akihiko
|
| Descriptions |
内容の要約
|
| Language |
eng
|
| Resource Type | doctoral thesis |
| Access Rights | open access |
| Dissertation Number | 甲第9545号 |
| Degree Name | |
| Date of Granted | 2024-03-23 |
| Degree Grantors |
広島大学
Hiroshima University
|
