Human glioblastoma arises from subventricular zone cells with low-level driver mutations
Glioblastoma (GBM) is a devastating and incurable brain tumour, with a median overall
survival of fifteen months 1 , 2 . Identifying the cell of origin that harbours mutations that drive …
survival of fifteen months 1 , 2 . Identifying the cell of origin that harbours mutations that drive …
[HTML][HTML] Federated learning enables big data for rare cancer boundary detection
Although machine learning (ML) has shown promise across disciplines, out-of-sample
generalizability is concerning. This is currently addressed by sharing multi-site data, but such …
generalizability is concerning. This is currently addressed by sharing multi-site data, but such …
Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics
YS Choi, S Bae, JH Chang, SG Kang, SH Kim… - Neuro …, 2021 - academic.oup.com
Background Glioma prognosis depends on isocitrate dehydrogenase (IDH) mutation status.
We aimed to predict the IDH status of gliomas from preoperative MR images using a fully …
We aimed to predict the IDH status of gliomas from preoperative MR images using a fully …
Radiomic MRI phenotyping of glioblastoma: improving survival prediction
Purpose To investigate whether radiomic features at MRI improve survival prediction in
patients with glioblastoma multiforme (GBM) when they are integrated with clinical and genetic …
patients with glioblastoma multiforme (GBM) when they are integrated with clinical and genetic …
Analysis of radiosurgical results in patients with brain metastases according to the number of brain lesions: is stereotactic radiosurgery effective for multiple brain …
WS Chang, HY Kim, JW Chang, YG Park… - Journal of …, 2010 - thejns.org
… R01-2008-000-20545-0) to Jong Hee Chang. The authors report no con flict of interest
concerning the materials or methods used in this study or the findings specified in this paper. …
concerning the materials or methods used in this study or the findings specified in this paper. …
Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging
Objectives Preoperative, noninvasive prediction of the meningioma grade is important because
it influences the treatment strategy. The purpose of this study was to evaluate the role of …
it influences the treatment strategy. The purpose of this study was to evaluate the role of …
Bilateral anterior cingulotomy for refractory obsessive-compulsive disorder: long-term follow-up results
…, JH Chang, YG Park, SS Chung, JW Chang - Stereotactic and …, 2006 - karger.com
Objective: To investigate the long-term efficacy and adverse cognitive effects of stereotactic
bilateral anterior cingulotomy as a treatment for refractory obsessive-compulsive disorder (…
bilateral anterior cingulotomy as a treatment for refractory obsessive-compulsive disorder (…
Microvascular decompression for hemifacial spasm: a long-term follow-up of 1,169 consecutive cases
SS Chung, JH Chang, JY Choi, JW Chang… - Stereotactic and …, 2002 - karger.com
We analyzed the records of 1,169 patients with hemifacial spasm (HFS) who underwent
microvascular decompression (MVD) and were followed up for more than 6 months from …
microvascular decompression (MVD) and were followed up for more than 6 months from …
[HTML][HTML] Terahertz reflectometry imaging for low and high grade gliomas
…, SH Kim, JH Lee, SJ Haam, YM Huh, JH Chang… - Scientific reports, 2016 - nature.com
Gross total resection (GTR) of glioma is critical for improving the survival rate of glioma
patients. One of the greatest challenges for achieving GTR is the difficulty in discriminating low …
patients. One of the greatest challenges for achieving GTR is the difficulty in discriminating low …
Primary central nervous system lymphoma and atypical glioblastoma: differentiation using radiomics approach
Objectives To evaluate the diagnostic performance of magnetic resonance (MR) radiomics-based
machine-learning algorithms in differentiating primary central nervous system …
machine-learning algorithms in differentiating primary central nervous system …