232 related articles for article (PubMed ID: 34214211)
1. Utility of radiomic zones for risk classification and clinical outcome predictions using supervised machine learning during simultaneous
Tu SJ; Tran VT; Teo JM; Chong WC; Tseng JR
Med Phys; 2021 Sep; 48(9):5192-5201. PubMed ID: 34214211
[TBL] [Abstract][Full Text] [Related]
2. More advantages in detecting bone and soft tissue metastases from prostate cancer using
Pianou NK; Stavrou PZ; Vlontzou E; Rondogianni P; Exarhos DN; Datseris IE
Hell J Nucl Med; 2019; 22(1):6-9. PubMed ID: 30843003
[TBL] [Abstract][Full Text] [Related]
3. Comparison of machine learning algorithms to predict clinically significant prostate cancer of the peripheral zone with multiparametric MRI using clinical assessment categories and radiomic features.
Bernatz S; Ackermann J; Mandel P; Kaltenbach B; Zhdanovich Y; Harter PN; Döring C; Hammerstingl R; Bodelle B; Smith K; Bucher A; Albrecht M; Rosbach N; Basten L; Yel I; Wenzel M; Bankov K; Koch I; Chun FK; Köllermann J; Wild PJ; Vogl TJ
Eur Radiol; 2020 Dec; 30(12):6757-6769. PubMed ID: 32676784
[TBL] [Abstract][Full Text] [Related]
4. Comparison of quantitative parameters and radiomic features as inputs into machine learning models to predict the Gleason score of prostate cancer lesions.
Nai YH; Cheong DLH; Roy S; Kok T; Stephenson MC; Schaefferkoetter J; Totman JJ; Conti M; Eriksson L; Robins EG; Wang Z; Chua WY; Ang BWL; Singha AK; Thamboo TP; Chiong E; Reilhac A
Magn Reson Imaging; 2023 Jul; 100():64-72. PubMed ID: 36933775
[TBL] [Abstract][Full Text] [Related]
5. Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.
Abdollahi H; Mofid B; Shiri I; Razzaghdoust A; Saadipoor A; Mahdavi A; Galandooz HM; Mahdavi SR
Radiol Med; 2019 Jun; 124(6):555-567. PubMed ID: 30607868
[TBL] [Abstract][Full Text] [Related]
6. Voxel-based supervised machine learning of peripheral zone prostate cancer using noncontrast multiparametric MRI.
Gholizadeh N; Simpson J; Ramadan S; Denham J; Lau P; Siddique S; Dowling J; Welsh J; Chalup S; Greer PB
J Appl Clin Med Phys; 2020 Oct; 21(10):179-191. PubMed ID: 32770600
[TBL] [Abstract][Full Text] [Related]
7. Radiomics analysis of 18F-Choline PET/CT in the prediction of disease outcome in high-risk prostate cancer: an explorative study on machine learning feature classification in 94 patients.
Alongi P; Stefano A; Comelli A; Laudicella R; Scalisi S; Arnone G; Barone S; Spada M; Purpura P; Bartolotta TV; Midiri M; Lagalla R; Russo G
Eur Radiol; 2021 Jul; 31(7):4595-4605. PubMed ID: 33443602
[TBL] [Abstract][Full Text] [Related]
8. Machine learning-based analysis of [
Cysouw MCF; Jansen BHE; van de Brug T; Oprea-Lager DE; Pfaehler E; de Vries BM; van Moorselaar RJA; Hoekstra OS; Vis AN; Boellaard R
Eur J Nucl Med Mol Imaging; 2021 Feb; 48(2):340-349. PubMed ID: 32737518
[TBL] [Abstract][Full Text] [Related]
9. Machine learning predictive performance evaluation of conventional and fuzzy radiomics in clinical cancer imaging cohorts.
Grahovac M; Spielvogel CP; Krajnc D; Ecsedi B; Traub-Weidinger T; Rasul S; Kluge K; Zhao M; Li X; Hacker M; Haug A; Papp L
Eur J Nucl Med Mol Imaging; 2023 May; 50(6):1607-1620. PubMed ID: 36738311
[TBL] [Abstract][Full Text] [Related]
10.
Li P; Wang X; Xu C; Liu C; Zheng C; Fulham MJ; Feng D; Wang L; Song S; Huang G
Eur J Nucl Med Mol Imaging; 2020 May; 47(5):1116-1126. PubMed ID: 31982990
[TBL] [Abstract][Full Text] [Related]
11. The role of [
Basso Dias A; Mirshahvalad SA; Ortega C; Perlis N; Berlin A; van der Kwast T; Ghai S; Jhaveri K; Metser U; Haider M; Avery L; Veit-Haibach P
Eur J Nucl Med Mol Imaging; 2023 Jun; 50(7):2167-2176. PubMed ID: 36809425
[TBL] [Abstract][Full Text] [Related]
12. Clinical utility of (18)F-fluorocholine positron-emission tomography/computed tomography (PET/CT) in biochemical relapse of prostate cancer after radical treatment: results of a multicentre study.
Rodado-Marina S; Coronado-Poggio M; García-Vicente AM; García-Garzón JR; Alonso-Farto JC; de la Jara AC; Maldonado-Suárez A; Rodríguez-Fernández A
BJU Int; 2015 Jun; 115(6):874-83. PubMed ID: 25307619
[TBL] [Abstract][Full Text] [Related]
13. Prediction of Gleason score in prostate cancer patients based on radiomic features of transrectal ultrasound images.
Cheng T; Li H
Br J Radiol; 2024 Feb; 97(1154):415-421. PubMed ID: 38308030
[TBL] [Abstract][Full Text] [Related]
14. Radiomic-based machine learning model for the accurate prediction of prostate cancer risk stratification.
Shu X; Liu Y; Qiao X; Ai G; Liu L; Liao J; Deng Z; He X
Br J Radiol; 2023 Mar; 96(1143):20220238. PubMed ID: 36475858
[TBL] [Abstract][Full Text] [Related]
15. Radiomic features for prostate cancer detection on MRI differ between the transition and peripheral zones: Preliminary findings from a multi-institutional study.
Ginsburg SB; Algohary A; Pahwa S; Gulani V; Ponsky L; Aronen HJ; Boström PJ; Böhm M; Haynes AM; Brenner P; Delprado W; Thompson J; Pulbrock M; Taimen P; Villani R; Stricker P; Rastinehad AR; Jambor I; Madabhushi A
J Magn Reson Imaging; 2017 Jul; 46(1):184-193. PubMed ID: 27990722
[TBL] [Abstract][Full Text] [Related]
16. Magnetic resonance imaging radiomics predicts preoperative axillary lymph node metastasis to support surgical decisions and is associated with tumor microenvironment in invasive breast cancer: A machine learning, multicenter study.
Yu Y; He Z; Ouyang J; Tan Y; Chen Y; Gu Y; Mao L; Ren W; Wang J; Lin L; Wu Z; Liu J; Ou Q; Hu Q; Li A; Chen K; Li C; Lu N; Li X; Su F; Liu Q; Xie C; Yao H
EBioMedicine; 2021 Jul; 69():103460. PubMed ID: 34233259
[TBL] [Abstract][Full Text] [Related]
17. Choline PET/CT features to predict survival outcome in high-risk prostate cancer restaging: a preliminary machine-learning radiomics study.
Alongi P; Laudicella R; Stefano A; Caobelli F; Comelli A; Vento A; Sardina D; Ganduscio G; Toia P; Ceci F; Mapelli P; Picchio M; Midiri M; Baldari S; Lagalla R; Russo G
Q J Nucl Med Mol Imaging; 2022 Dec; 66(4):352-360. PubMed ID: 32543166
[TBL] [Abstract][Full Text] [Related]
18. Can machine learning models improve early detection of brain metastases using diffusion weighted imaging-based radiomics?
Madamesila J; Tchistiakova E; Faruqi S; Das S; Ploquin N
Quant Imaging Med Surg; 2023 Dec; 13(12):7706-7718. PubMed ID: 38106308
[TBL] [Abstract][Full Text] [Related]
19. Radiomic Machine Learning for Characterization of Prostate Lesions with MRI: Comparison to ADC Values.
Bonekamp D; Kohl S; Wiesenfarth M; Schelb P; Radtke JP; Götz M; Kickingereder P; Yaqubi K; Hitthaler B; Gählert N; Kuder TA; Deister F; Freitag M; Hohenfellner M; Hadaschik BA; Schlemmer HP; Maier-Hein KH
Radiology; 2018 Oct; 289(1):128-137. PubMed ID: 30063191
[TBL] [Abstract][Full Text] [Related]
20.
Tran VT; Tu SJ; Tseng JR
Cancers (Basel); 2022 Oct; 14(19):. PubMed ID: 36230761
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]