211 related articles for article (PubMed ID: 34754658)
1. The Role of Machine Learning and Radiomics for Treatment Response Prediction in Idiopathic Normal Pressure Hydrocephalus.
Sotoudeh H; Sadaatpour Z; Rezaei A; Shafaat O; Sotoudeh E; Tabatabaie M; Singhal A; Tanwar M
Cureus; 2021 Oct; 13(10):e18497. PubMed ID: 34754658
[TBL] [Abstract][Full Text] [Related]
2. Utility of MRI-based disproportionately enlarged subarachnoid space hydrocephalus scoring for predicting prognosis after surgery for idiopathic normal pressure hydrocephalus: clinical research.
Shinoda N; Hirai O; Hori S; Mikami K; Bando T; Shimo D; Kuroyama T; Kuramoto Y; Matsumoto M; Ueno Y
J Neurosurg; 2017 Dec; 127(6):1436-1442. PubMed ID: 28156249
[TBL] [Abstract][Full Text] [Related]
3. A combined radiomics and clinical variables model for prediction of malignancy in T2 hyperintense uterine mesenchymal tumors on MRI.
Wang T; Gong J; Li Q; Chu C; Shen W; Peng W; Gu Y; Li W
Eur Radiol; 2021 Aug; 31(8):6125-6135. PubMed ID: 33486606
[TBL] [Abstract][Full Text] [Related]
4. One-year outcome in patients with idiopathic normal-pressure hydrocephalus: comparison of lumboperitoneal shunt to ventriculoperitoneal shunt.
Miyajima M; Kazui H; Mori E; Ishikawa M;
J Neurosurg; 2016 Dec; 125(6):1483-1492. PubMed ID: 26871203
[TBL] [Abstract][Full Text] [Related]
5. Disability risk or unimproved symptoms following shunt surgery in patients with idiopathic normal-pressure hydrocephalus: post hoc analysis of SINPHONI-2.
Yamada S; Kimura T; Jingami N; Atsuchi M; Hirai O; Tokuda T; Miyajima M; Kazui H; Mori E; Ishikawa M;
J Neurosurg; 2017 Jun; 126(6):2002-2009. PubMed ID: 27419822
[TBL] [Abstract][Full Text] [Related]
6. Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.
Wang X; Wan Q; Chen H; Li Y; Li X
Eur Radiol; 2020 Aug; 30(8):4595-4605. PubMed ID: 32222795
[TBL] [Abstract][Full Text] [Related]
7. Prognostic prediction of hypertensive intracerebral hemorrhage using CT radiomics and machine learning.
Xu X; Zhang J; Yang K; Wang Q; Chen X; Xu B
Brain Behav; 2021 May; 11(5):e02085. PubMed ID: 33624945
[TBL] [Abstract][Full Text] [Related]
8. Prediction of High-Risk Cytogenetic Status in Multiple Myeloma Based on Magnetic Resonance Imaging: Utility of Radiomics and Comparison of Machine Learning Methods.
Liu J; Zeng P; Guo W; Wang C; Geng Y; Lang N; Yuan H
J Magn Reson Imaging; 2021 Oct; 54(4):1303-1311. PubMed ID: 33979466
[TBL] [Abstract][Full Text] [Related]
9. Machine Learning Assisted MRI Characterization for Diagnosis of Neonatal Acute Bilirubin Encephalopathy.
Liu Z; Ji B; Zhang Y; Cui G; Liu L; Man S; Ding L; Yang X; Mao H; Wang L
Front Neurol; 2019; 10():1018. PubMed ID: 31632332
[No Abstract] [Full Text] [Related]
10. Utilization of radiomics to predict long-term outcome of magnetic resonance-guided focused ultrasound ablation therapy in adenomyosis.
Li Z; Zhang J; Song Y; Yin X; Chen A; Tang N; Prince MR; Yang G; Wang H
Eur Radiol; 2021 Jan; 31(1):392-402. PubMed ID: 32725335
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Magnetic Resonance Imaging Radiomics-Based Machine Learning Prediction of Clinically Significant Prostate Cancer in Equivocal PI-RADS 3 Lesions.
Hectors SJ; Chen C; Chen J; Wang J; Gordon S; Yu M; Al Hussein Al Awamlh B; Sabuncu MR; Margolis DJA; Hu JC
J Magn Reson Imaging; 2021 Nov; 54(5):1466-1473. PubMed ID: 33970516
[TBL] [Abstract][Full Text] [Related]
13. Cortical atrophy distinguishes idiopathic normal-pressure hydrocephalus from progressive supranuclear palsy: A machine learning approach.
Bianco MG; Quattrone A; Sarica A; Vescio B; Buonocore J; Vaccaro MG; Aracri F; Calomino C; Gramigna V; Quattrone A
Parkinsonism Relat Disord; 2022 Oct; 103():7-14. PubMed ID: 35988437
[TBL] [Abstract][Full Text] [Related]
14. Non-contrast CT radiomics and machine learning for outcomes prediction of patients with acute ischemic stroke receiving conventional treatment.
Zhang L; Wu J; Yu R; Xu R; Yang J; Fan Q; Wang D; Zhang W
Eur J Radiol; 2023 Aug; 165():110959. PubMed ID: 37437435
[TBL] [Abstract][Full Text] [Related]
15. Treatment effect prediction for sarcoma patients treated with preoperative radiotherapy using radiomics features from longitudinal diffusion-weighted MRIs.
Gao Y; Kalbasi A; Hsu W; Ruan D; Fu J; Shao J; Cao M; Wang C; Eilber FC; Bernthal N; Bukata S; Dry SM; Nelson SD; Kamrava M; Lewis J; Low DA; Steinberg M; Hu P; Yang Y
Phys Med Biol; 2020 Aug; 65(17):175006. PubMed ID: 32554891
[TBL] [Abstract][Full Text] [Related]
16. Soft Tissue Sarcomas: Preoperative Predictive Histopathological Grading Based on Radiomics of MRI.
Zhang Y; Zhu Y; Shi X; Tao J; Cui J; Dai Y; Zheng M; Wang S
Acad Radiol; 2019 Sep; 26(9):1262-1268. PubMed ID: 30377057
[TBL] [Abstract][Full Text] [Related]
17. Comparison of machine learning classifiers for differentiation of grade 1 from higher gradings in meningioma: A multicenter radiomics study.
Hamerla G; Meyer HJ; Schob S; Ginat DT; Altman A; Lim T; Gihr GA; Horvath-Rizea D; Hoffmann KT; Surov A
Magn Reson Imaging; 2019 Nov; 63():244-249. PubMed ID: 31425811
[TBL] [Abstract][Full Text] [Related]
18. Machine Learning-based Analysis of Rectal Cancer MRI Radiomics for Prediction of Metachronous Liver Metastasis.
Liang M; Cai Z; Zhang H; Huang C; Meng Y; Zhao L; Li D; Ma X; Zhao X
Acad Radiol; 2019 Nov; 26(11):1495-1504. PubMed ID: 30711405
[TBL] [Abstract][Full Text] [Related]
19. Default mode network connectivity in patients with idiopathic normal pressure hydrocephalus.
Khoo HM; Kishima H; Tani N; Oshino S; Maruo T; Hosomi K; Yanagisawa T; Kazui H; Watanabe Y; Shimokawa T; Aso T; Kawaguchi A; Yamashita F; Saitoh Y; Yoshimine T
J Neurosurg; 2016 Feb; 124(2):350-8. PubMed ID: 26295919
[TBL] [Abstract][Full Text] [Related]
20. Machine Learning-Based Radiomics of the Optic Chiasm Predict Visual Outcome Following Pituitary Adenoma Surgery.
Zhang Y; Chen C; Huang W; Cheng Y; Teng Y; Zhang L; Xu J
J Pers Med; 2021 Sep; 11(10):. PubMed ID: 34683132
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]