71 related articles for article (PubMed ID: 34296969)
1. Combining MRI and Histologic Imaging Features for Predicting Overall Survival in Patients with Glioma.
Rathore S; Chaddad A; Iftikhar MA; Bilello M; Abdulkadir A
Radiol Imaging Cancer; 2021 Jul; 3(4):e200108. PubMed ID: 34296969
[TBL] [Abstract][Full Text] [Related]
2. A metric for quantitative evaluation of glioma margin changes in magnetic resonance imaging.
Hu B; Zhang Z; Chen S; Xu Q; Li J
Acta Radiol; 2024 Jun; 65(6):645-653. PubMed ID: 38449078
[TBL] [Abstract][Full Text] [Related]
3. Outcome Prediction for Patient with High-Grade Gliomas from Brain Functional and Structural Networks.
Liu L; Zhang H; Rekik I; Chen X; Wang Q; Shen D
Med Image Comput Comput Assist Interv; 2016 Oct; 9901():26-34. PubMed ID: 28649677
[TBL] [Abstract][Full Text] [Related]
4. Grading of Gliomas by Contrast-Enhanced CT Radiomics Features.
Maskani M; Abbasi S; Etemad-Rezaee H; Abdolahi H; Zamanpour A; Montazerabadi A
J Biomed Phys Eng; 2024 Apr; 14(2):151-158. PubMed ID: 38628893
[TBL] [Abstract][Full Text] [Related]
5. Machine learning prediction of neurocognitive impairment among people with HIV using clinical and multimodal magnetic resonance imaging data.
Xu Y; Lin Y; Bell RP; Towe SL; Pearson JM; Nadeem T; Chan C; Meade CS
J Neurovirol; 2021 Feb; 27(1):1-11. PubMed ID: 33464541
[TBL] [Abstract][Full Text] [Related]
6. Deep Neural Network Analysis of Pathology Images With Integrated Molecular Data for Enhanced Glioma Classification and Grading.
Pei L; Jones KA; Shboul ZA; Chen JY; Iftekharuddin KM
Front Oncol; 2021; 11():668694. PubMed ID: 34277415
[TBL] [Abstract][Full Text] [Related]
7. New Enhancement beyond Radiation Field Improves Survival Prediction in Patients with Post-Treatment High-Grade Glioma.
Yuan T; Ji X; Liu Y; Gao G; Ren JL; Huang D; Quan G
J Oncol; 2021; 2021():9437090. PubMed ID: 34035813
[TBL] [Abstract][Full Text] [Related]
8. Glioma Grading Using Cell Nuclei Morphologic Features in Digital Pathology Images.
Reza SM; Iftekharuddin KM
Proc SPIE Int Soc Opt Eng; 2016 Feb; 9785():. PubMed ID: 27942094
[TBL] [Abstract][Full Text] [Related]
9. Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.
Luckett PH; Olufawo MO; Park KY; Lamichhane B; Dierker D; Verastegui GT; Lee JJ; Yang P; Kim A; Butt OH; Chheda MG; Snyder AZ; Shimony JS; Leuthardt EC
J Neurooncol; 2024 May; ():. PubMed ID: 38789843
[TBL] [Abstract][Full Text] [Related]
10. Brain tumor grading diagnosis using transfer learning based on optical coherence tomography.
Hsu SPC; Lin MH; Lin CF; Hsiao TY; Wang YM; Sun CW
Biomed Opt Express; 2024 Apr; 15(4):2343-2357. PubMed ID: 38633066
[TBL] [Abstract][Full Text] [Related]
11. A model for accurate histopathologic assessment refines treatment options.
Sugarbaker PH; Van der Speeten K
J Gastrointest Oncol; 2021 Apr; 12(Suppl 1):S230. PubMed ID: 33970168
[No Abstract] [Full Text] [Related]
12. Pathomic model based on histopathological features and machine learning to predict IDO1 status and its association with breast cancer prognosis.
Zhuo X; Deng H; Qiu M; Qiu X
Breast Cancer Res Treat; 2024 May; ():. PubMed ID: 38780888
[TBL] [Abstract][Full Text] [Related]
13. An integrated radiology-pathology machine learning classifier for outcome prediction following radical prostatectomy: Preliminary findings.
Hiremath A; Corredor G; Li L; Leo P; Magi-Galluzzi C; Elliott R; Purysko A; Shiradkar R; Madabhushi A
Heliyon; 2024 Apr; 10(8):e29602. PubMed ID: 38665576
[TBL] [Abstract][Full Text] [Related]
14. Added prognostic value of 3D deep learning-derived features from preoperative MRI for adult-type diffuse gliomas.
Lee JO; Ahn SS; Choi KS; Lee J; Jang J; Park JH; Hwang I; Park CK; Park SH; Chung JW; Choi SH
Neuro Oncol; 2024 Mar; 26(3):571-580. PubMed ID: 37855826
[TBL] [Abstract][Full Text] [Related]
15. Radio-pathomic approaches in pediatric neuro-oncology: Opportunities and challenges.
Familiar AM; Mahtabfar A; Fathi Kazerooni A; Kiani M; Vossough A; Viaene A; Storm PB; Resnick AC; Nabavizadeh A
Neurooncol Adv; 2023; 5(1):vdad119. PubMed ID: 37841693
[TBL] [Abstract][Full Text] [Related]
16. New insights into glioma frequency maps: From genetic and transcriptomic correlate to survival prediction.
Bao H; Ren P; Yi L; Lv Z; Ding W; Li C; Li S; Li Z; Yang X; Liang X; Liang P
Int J Cancer; 2023 Mar; 152(5):998-1012. PubMed ID: 36305649
[TBL] [Abstract][Full Text] [Related]
17. Artificial intelligence in oncologic imaging.
Chen MM; Terzic A; Becker AS; Johnson JM; Wu CC; Wintermark M; Wald C; Wu J
Eur J Radiol Open; 2022; 9():100441. PubMed ID: 36193451
[TBL] [Abstract][Full Text] [Related]
18. Predicting Survival in Patients with Brain Tumors: Current State-of-the-Art of AI Methods Applied to MRI.
di Noia C; Grist JT; Riemer F; Lyasheva M; Fabozzi M; Castelli M; Lodi R; Tonon C; Rundo L; Zaccagna F
Diagnostics (Basel); 2022 Sep; 12(9):. PubMed ID: 36140526
[TBL] [Abstract][Full Text] [Related]
19. Ensembles of Convolutional Neural Networks for Survival Time Estimation of High-Grade Glioma Patients from Multimodal MRI.
Ben Ahmed K; Hall LO; Goldgof DB; Gatenby R
Diagnostics (Basel); 2022 Jan; 12(2):. PubMed ID: 35204436
[TBL] [Abstract][Full Text] [Related]
20. AI-Driven Image Analysis in Central Nervous System Tumors-Traditional Machine Learning, Deep Learning and Hybrid Models.
Krauze AV; Zhuge Y; Zhao R; Tasci E; Camphausen K
J Biotechnol Biomed; 2022; 5(1):1-19. PubMed ID: 35106480
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
