PubMed Mentions
The links below are to publications on PubMed referring to XNAT. This list is gathered weekly from PubMed automatically.
| Publication/References | |
| New Therapeutics in Alzheimer's Disease Longitudinal Cohort study (NTAD): study protocol. Description: Lanskey, Juliette Helene, et al. New Therapeutics in Alzheimer's Disease Longitudinal Cohort study (NTAD): study protocol. ''BMJ Open''. 2022 Dec 15; '''12''' (12):e055135 | |
| Computed tomography and magnetic resonance imaging approaches to Graves' ophthalmopathy: a narrative review. Description: Luccas, Rafael, et al. Computed tomography and magnetic resonance imaging approaches to Graves' ophthalmopathy: a narrative review. ''Front Endocrinol (Lausanne)''. 2023; '''14''': 1277961 | |
| Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study. Description: Orton, Matthew R, et al. Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study. ''Cancer Imaging''. 2023 Aug 14; '''23''' (1):76 | |
| Assessment of longitudinal brain development using super-resolution magnetic resonance imaging following fetal surgery for open spina bifida. Description: Mufti, N, et al. Assessment of longitudinal brain development using super-resolution magnetic resonance imaging following fetal surgery for open spina bifida. ''Ultrasound Obstet Gynecol''. 2023 Nov; '''62''' (5):707-720 | |
| Factors influencing the reliability of a CT angiography-based deep learning method for infarct volume estimation. Description: Hokkinen, Lasse, et al. Factors influencing the reliability of a CT angiography-based deep learning method for infarct volume estimation. ''BJR Open''. 2024 Jan; '''6''' (1):tzae001 | |
| Image annotation and curation in radiology: an overview for machine learning practitioners. Description: Galbusera, Fabio, et al. Image annotation and curation in radiology: an overview for machine learning practitioners. ''Eur Radiol Exp''. 2024 Feb 6; '''8''' (1):11 | |
| Clinical application of machine learning models in patients with prostate cancer before prostatectomy. Description: Guerra, Adalgisa, et al. Clinical application of machine learning models in patients with prostate cancer before prostatectomy. ''Cancer Imaging''. 2024 Feb 8; '''24''' (1):24 |