174 related articles for article (PubMed ID: 33394142)
1. Optimisation and evaluation of the random forest model in the efficacy prediction of chemoradiotherapy for advanced cervical cancer based on radiomics signature from high-resolution T2 weighted images.
Liu D; Zhang X; Zheng T; Shi Q; Cui Y; Wang Y; Liu L
Arch Gynecol Obstet; 2021 Mar; 303(3):811-820. PubMed ID: 33394142
[TBL] [Abstract][Full Text] [Related]
2. Radiomics-based prediction of two-year clinical outcome in locally advanced cervical cancer patients undergoing neoadjuvant chemoradiotherapy.
Autorino R; Gui B; Panza G; Boldrini L; Cusumano D; Russo L; Nardangeli A; Persiani S; Campitelli M; Ferrandina G; Macchia G; Valentini V; Gambacorta MA; Manfredi R
Radiol Med; 2022 May; 127(5):498-506. PubMed ID: 35325372
[TBL] [Abstract][Full Text] [Related]
3. Hysterectomy with radiotherapy or chemotherapy or both for women with locally advanced cervical cancer.
Kokka F; Bryant A; Brockbank E; Powell M; Oram D
Cochrane Database Syst Rev; 2015 Apr; (4):CD010260. PubMed ID: 25847525
[TBL] [Abstract][Full Text] [Related]
4. Radiomics analysis of multiparametric MRI for prediction of pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal cancer.
Cui Y; Yang X; Shi Z; Yang Z; Du X; Zhao Z; Cheng X
Eur Radiol; 2019 Mar; 29(3):1211-1220. PubMed ID: 30128616
[TBL] [Abstract][Full Text] [Related]
5. MR Imaging of Rectal Cancer: Radiomics Analysis to Assess Treatment Response after Neoadjuvant Therapy.
Horvat N; Veeraraghavan H; Khan M; Blazic I; Zheng J; Capanu M; Sala E; Garcia-Aguilar J; Gollub MJ; Petkovska I
Radiology; 2018 Jun; 287(3):833-843. PubMed ID: 29514017
[TBL] [Abstract][Full Text] [Related]
6. Selecting Candidates for Organ-Preserving Strategies After Neoadjuvant Chemoradiotherapy for Rectal Cancer: Development and Validation of a Model Integrating MRI Radiomics and Pathomics.
Wan L; Sun Z; Peng W; Wang S; Li J; Zhao Q; Wang S; Ouyang H; Zhao X; Zou S; Zhang H
J Magn Reson Imaging; 2022 Oct; 56(4):1130-1142. PubMed ID: 35142001
[TBL] [Abstract][Full Text] [Related]
7. Magnetic resonance imaging features of tumor and lymph node to predict clinical outcome in node-positive cervical cancer: a retrospective analysis.
Park SH; Hahm MH; Bae BK; Chong GO; Jeong SY; Na S; Jeong S; Kim JC
Radiat Oncol; 2020 Apr; 15(1):86. PubMed ID: 32312283
[TBL] [Abstract][Full Text] [Related]
8. Prediction of out-of-field recurrence after chemoradiotherapy for cervical cancer using a combination model of clinical parameters and magnetic resonance imaging radiomics: a multi-institutional study of the Japanese Radiation Oncology Study Group.
Ikushima H; Haga A; Ando K; Kato S; Kaneyasu Y; Uno T; Okonogi N; Yoshida K; Ariga T; Isohashi F; Harima Y; Kanemoto A; Ii N; Wakatsuki M; Ohno T
J Radiat Res; 2022 Jan; 63(1):98-106. PubMed ID: 34865079
[TBL] [Abstract][Full Text] [Related]
9. Predictive value of diffusion-weighted magnetic resonance imaging during chemoradiotherapy for uterine cervical cancer.
Makino H; Kato H; Furui T; Morishige K; Kanematsu M
J Obstet Gynaecol Res; 2014 Apr; 40(4):1098-104. PubMed ID: 24320754
[TBL] [Abstract][Full Text] [Related]
10. Delta radiomics analysis for prediction of intermediary- and high-risk factors for patients with locally advanced cervical cancer receiving neoadjuvant therapy.
Wu RR; Zhou YM; Xie XY; Chen JY; Quan KR; Wei YT; Xia XY; Chen WJ
Sci Rep; 2023 Nov; 13(1):19409. PubMed ID: 37938596
[TBL] [Abstract][Full Text] [Related]
11. [A prediction model of pathological complete response in patients with locally advanced rectal cancer after PD-1 antibody combined with total neoadjuvant chemoradiotherapy based on MRI radiomics].
Zhang XY; Zhu HT; Li XT; Li YJ; Li ZW; Wang WH; Wu AW; Sun YS; Zhang L
Zhonghua Wei Chang Wai Ke Za Zhi; 2022 Mar; 25(3):228-234. PubMed ID: 35340172
[No Abstract] [Full Text] [Related]
12. Neoadjuvant chemotherapy followed by radical surgery versus concurrent chemoradiotherapy in patients with FIGO stage IIB cervical cancer: the CSEM 006 study.
Tu H; Huang H; Ouyang Y; Liu Q; Xian B; Song K; Chen G; Shen Y; Liu J
Int J Gynecol Cancer; 2021 Jan; 31(1):129-133. PubMed ID: 32522771
[TBL] [Abstract][Full Text] [Related]
13. Radiomic analysis for pretreatment prediction of response to neoadjuvant chemotherapy in locally advanced cervical cancer: A multicentre study.
Sun C; Tian X; Liu Z; Li W; Li P; Chen J; Zhang W; Fang Z; Du P; Duan H; Liu P; Wang L; Chen C; Tian J
EBioMedicine; 2019 Aug; 46():160-169. PubMed ID: 31395503
[TBL] [Abstract][Full Text] [Related]
14. MRI-based radiomics value for predicting the survival of patients with locally advanced cervical squamous cell cancer treated with concurrent chemoradiotherapy.
Zhang X; Zhao J; Zhang Q; Wang S; Zhang J; An J; Xie L; Yu X; Zhao X
Cancer Imaging; 2022 Jul; 22(1):35. PubMed ID: 35842679
[TBL] [Abstract][Full Text] [Related]
15. Predicting pathological complete response by comparing MRI-based radiomics pre- and postneoadjuvant radiotherapy for locally advanced rectal cancer.
Li Y; Liu W; Pei Q; Zhao L; Güngör C; Zhu H; Song X; Li C; Zhou Z; Xu Y; Wang D; Tan F; Yang P; Pei H
Cancer Med; 2019 Dec; 8(17):7244-7252. PubMed ID: 31642204
[TBL] [Abstract][Full Text] [Related]
16. MRI radiomics in overall survival prediction of local advanced cervical cancer patients tread by adjuvant chemotherapy following concurrent chemoradiotherapy or concurrent chemoradiotherapy alone.
Wei G; Jiang P; Tang Z; Qu A; Deng X; Guo F; Sun H; Zhang Y; Gu L; Zhang S; Mu W; Wang J; Tian J
Magn Reson Imaging; 2022 Sep; 91():81-90. PubMed ID: 35636572
[TBL] [Abstract][Full Text] [Related]
17. Pre-treatment ADC image-based random forest classifier for identifying resistant rectal adenocarcinoma to neoadjuvant chemoradiotherapy.
Yang C; Jiang ZK; Liu LH; Zeng MS
Int J Colorectal Dis; 2020 Jan; 35(1):101-107. PubMed ID: 31786652
[TBL] [Abstract][Full Text] [Related]
18. Multi-modal radiomics model to predict treatment response to neoadjuvant chemotherapy for locally advanced rectal cancer.
Li ZY; Wang XD; Li M; Liu XJ; Ye Z; Song B; Yuan F; Yuan Y; Xia CC; Zhang X; Li Q
World J Gastroenterol; 2020 May; 26(19):2388-2402. PubMed ID: 32476800
[TBL] [Abstract][Full Text] [Related]
19. Evaluation of early regression index as response predictor in cervical cancer: A retrospective study on T2 and DWI MR images.
Cusumano D; Russo L; Gui B; Autorino R; Boldrini L; D'Erme L; Persiani S; Catucci F; Broggi S; Panza G; Nardangeli A; Campitelli M; Ferrandina G; Macchia G; Fiorino C; Valentini V; Scambia G; Manfredi R; Gambacorta MA
Radiother Oncol; 2022 Sep; 174():30-36. PubMed ID: 35811004
[TBL] [Abstract][Full Text] [Related]
20. Radiomics of locally advanced rectal cancer: machine learning-based prediction of response to neoadjuvant chemoradiotherapy using pre-treatment sagittal T2-weighted MRI.
Yardimci AH; Kocak B; Sel I; Bulut H; Bektas CT; Cin M; Dursun N; Bektas H; Mermut O; Yardimci VH; Kilickesmez O
Jpn J Radiol; 2023 Jan; 41(1):71-82. PubMed ID: 35962933
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
