文献
J-GLOBAL ID:202202262371952837
整理番号:22A0625060
子宮頸癌患者の予後を予測するための臨床および前処理18F-FDG-PET/CTラジオミック特徴の機械学習に基づく評価【JST・京大機械翻訳】
Machine learning based evaluation of clinical and pretreatment 18F-FDG-PET/CT radiomic features to predict prognosis of cervical cancer patients
著者 (9件):
Nakajo Masatoyo
(Department of Radiology, Kagoshima University, Graduate School of Medical and Dental Sciences, Kagoshima, Japan)
,
Jinguji Megumi
(Department of Radiology, Kagoshima University, Graduate School of Medical and Dental Sciences, Kagoshima, Japan)
,
Tani Atsushi
(Department of Radiology, Kagoshima University, Graduate School of Medical and Dental Sciences, Kagoshima, Japan)
,
Yano Erina
(Department of Radiology, Kagoshima University, Graduate School of Medical and Dental Sciences, Kagoshima, Japan)
,
Hoo Chin Khang
(Department of Radiology, Kagoshima University, Graduate School of Medical and Dental Sciences, Kagoshima, Japan)
,
Hirahara Daisuke
(Department of Management Planning Division, Harada Academy, Kagoshima, Japan)
,
Togami Shinichi
(Department of Obstetrics and Gynecology, Kagoshima University, Graduate School of Medical and Dental Sciences, Kagoshima, Japan)
,
Kobayashi Hiroaki
(Department of Obstetrics and Gynecology, Kagoshima University, Graduate School of Medical and Dental Sciences, Kagoshima, Japan)
,
Yoshiura Takashi
(Department of Radiology, Kagoshima University, Graduate School of Medical and Dental Sciences, Kagoshima, Japan)
資料名:
Abdominal Radiology
(Abdominal Radiology)
巻:
47
号:
2
ページ:
838-847
発行年:
2022年
JST資料番号:
W3979A
ISSN:
2366-0058
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
ドイツ (DEU)
言語:
英語 (EN)