Clinical application of machine learning models for brain imaging in epilepsy: a review
D Sone, I Beheshti - Frontiers in Neuroscience, 2021 - frontiersin.org
Epilepsy is a common neurological disorder characterized by recurrent and disabling
seizures. An increasing number of clinical and experimental applications of machine …
seizures. An increasing number of clinical and experimental applications of machine …
Artificial intelligence in epilepsy—applications and pathways to the clinic
Artificial intelligence (AI) is rapidly transforming health care, and its applications in epilepsy
have increased exponentially over the past decade. Integration of AI into epilepsy …
have increased exponentially over the past decade. Integration of AI into epilepsy …
Machine learning-based Radiomics analysis for differentiation degree and lymphatic node metastasis of extrahepatic cholangiocarcinoma
Y Tang, CM Yang, S Su, WJ Wang, LP Fan, J Shu - BMC cancer, 2021 - Springer
Background Radiomics may provide more objective and accurate predictions for
extrahepatic cholangiocarcinoma (ECC). In this study, we developed radiomics models …
extrahepatic cholangiocarcinoma (ECC). In this study, we developed radiomics models …
MRI‐Based Radiomics Approach for Differentiating Juvenile Myoclonic Epilepsy from Epilepsy with Generalized Tonic–Clonic Seizures Alone
Background The clinical presentation of juvenile myoclonic epilepsy (JME) and epilepsy
with generalized tonic–clonic seizures alone (GTCA) is similar, and MRI scans are often …
with generalized tonic–clonic seizures alone (GTCA) is similar, and MRI scans are often …
Preoperative MRI for postoperative seizure prediction: a radiomics study of dysembryoplastic neuroepithelial tumor and a systematic review
J Wang, X Luo, C Chen, J Deng, H Long, K Yang… - Neurosurgical …, 2022 - thejns.org
OBJECTIVE In this systematic review the authors aimed to evaluate the effectiveness and
superiority of radiomics in detecting tiny epilepsy lesions and to conduct original research in …
superiority of radiomics in detecting tiny epilepsy lesions and to conduct original research in …
[HTML][HTML] Multiparametric MRI: from simultaneous rapid acquisition methods and analysis techniques using scoring, machine learning, radiomics, and deep learning to …
With the recent advancements in rapid imaging methods, higher numbers of contrasts and
quantitative parameters can be acquired in less and less time. Some acquisition models …
quantitative parameters can be acquired in less and less time. Some acquisition models …
Predicting Drug Treatment Outcomes in Children with Tuberous Sclerosis Complex–Related Epilepsy: A Clinical Radiomics Study
Z Hu, D Jiang, X Zhao, J Yang… - American Journal …, 2023 - Am Soc Neuroradiology
BACKGROUND AND PURPOSE: Highly predictive markers of drug treatment outcomes of
tuberous sclerosis complex–related epilepsy are a key unmet clinical need. The objective of …
tuberous sclerosis complex–related epilepsy are a key unmet clinical need. The objective of …
Artificial intelligence for medical image analysis in epilepsy
J Sollee, L Tang, AB Igiraneza, B **ao, HX Bai… - Epilepsy Research, 2022 - Elsevier
Given improvements in computing power, artificial intelligence (AI) with deep learning has
emerged as the state-of-the art method for the analysis of medical imaging data and will …
emerged as the state-of-the art method for the analysis of medical imaging data and will …
Accurate lateralization and classification of MRI-negative 18F-FDG-PET-positive temporal lobe epilepsy using double inversion recovery and machine-learning
I Beheshti, D Sone, N Maikusa, Y Kimura… - Computers in Biology …, 2021 - Elsevier
Objective The main objective of this study was to determine the ability of double inversion
recovery (DIR) data coupled with machine-learning algorithms to distinguish normal …
recovery (DIR) data coupled with machine-learning algorithms to distinguish normal …
A quantitative imaging biomarker supporting radiological assessment of hippocampal sclerosis derived from deep learning-based segmentation of T1w-MRI
M Rebsamen, P Radojewski, R McKinley… - Frontiers in …, 2022 - frontiersin.org
Purpose Hippocampal volumetry is an important biomarker to quantify atrophy in patients
with mesial temporal lobe epilepsy. We investigate the sensitivity of automated …
with mesial temporal lobe epilepsy. We investigate the sensitivity of automated …