Automatic detection of interictal epileptiform discharges (IEDs, short as 'spikes') from an epileptic brain can help predict seizure recurrence and support the diagnosis of epilepsy. Developing fast, reliable and robust detection methods for IEDs bas...
OBJECTIVES: Epilepsy surgery is underutilized. Automating the identification of potential surgical candidates may facilitate earlier intervention. Our objective was to develop site-specific machine learning (ML) algorithms to identify candidates befo...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Mar 26, 2021
OBJECTIVE: Automating detection of Interictal Epileptiform Discharges (IEDs) in electroencephalogram (EEG) recordings can reduce the time spent on visual analysis for the diagnosis of epilepsy. Deep learning has shown potential for this purpose, but ...
BACKGROUND: Assistive automatic seizure detection can empower human annotators to shorten patient monitoring data review times. We present a proof-of-concept for a seizure detection system that is sensitive, automated, patient-specific, and tunable t...
IEEE/ACM transactions on computational biology and bioinformatics
Feb 3, 2021
Conventional classification models for epileptic EEG signal recognition need sufficient labeled samples as training dataset. In addition, when training and testing EEG signal samples are collected from different distributions, for example, due to dif...
International journal of neural systems
Jan 30, 2021
EEG is the gold standard for seizure detection in the newborn infant, but EEG interpretation in the preterm group is particularly challenging; trained experts are scarce and the task of interpreting EEG in real-time is arduous. Preterm infants are re...
Image labeling using convolutional neural networks (CNNs) are a template-free alternative to traditional morphometric techniques. We trained a 3D deep CNN to label the hippocampus and amygdala on whole brain 700 μm isotropic 3D MP2RAGE MRI acquired a...
AMIA ... Annual Symposium proceedings. AMIA Symposium
Jan 25, 2021
Continuous patient monitoring is essential to achieve an effective and optimal patient treatment in the intensive care unit. In the specific case of epilepsy it is the only way to achieve a correct diagnosis and a subsequent optimal medication plan i...
INTRODUCTION: The diagnosis of epilepsy takes a certain process, depending entirely on the attending physician. However, the human factor may cause erroneous diagnosis in the analysis of the EEG signal. In the past 2 decades, many advanced signal pro...
BMC medical informatics and decision making
Dec 24, 2020
Applying machine learning to healthcare sheds light on evidence-based decision making and has shown promises to improve healthcare by combining clinical knowledge and biomedical data. However, medicine and data science are not synchronized. Oftentime...
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