Publications
U-PASS: An uncertainty-guided deep learning pipeline for automated sleep staging. KU Leuven
With the increasing prevalence of machine learning in critical fields like healthcare, ensuring the safety and reliability of these systems is crucial. Estimating uncertainty plays a vital role in enhancing reliability by identifying areas of high and low confidence and reducing the risk of errors. This study introduces U-PASS, a specialized human-centered machine learning pipeline tailored for clinical applications, which effectively ...
Outcome of Epilepsy Surgery in MRI-Negative Patients Without Histopathologic Abnormalities in the Resected Tissue. KU Leuven
BACKGROUND AND OBJECTIVE: Patients with presumed nonlesional focal epilepsy-based on either MRI or histopathologic findings-have a lower success rate of epilepsy surgery compared with lesional patients. In this study, we aimed to characterize a large group of patients with focal epilepsy who underwent epilepsy surgery despite a normal MRI and had no lesion on histopathology. Determinants of their postoperative seizure outcomes were further ...
EANM practice guidelines for an appropriate use of PET and SPECT for patients with epilepsy KU Leuven
Epilepsy is one of the most frequent neurological conditions with an estimated prevalence of more than 50 million people worldwide and an annual incidence of two million. Although pharmacotherapy with anti-seizure medication (ASM) is the treatment of choice, ~30% of patients with epilepsy do not respond to ASM and become drug resistant. Focal epilepsy is the most frequent form of epilepsy. In patients with drug-resistant focal epilepsy, epilepsy ...
Ceftazidime-related neurotoxicity in a patient with renal impairment: a case report and literature review KU Leuven
PURPOSE: We present the case of a 67-year-old woman with severely reduced renal clearance suffering from ceftazidime-induced encephalopathy. Subsequently, we search the literature to review and describe the neurotoxicity of ceftazidime. METHODS: A search string was developed to search PubMed for relevant cases from which relevant information was extracted. Using the collected data a ROC analysis was performed in R to determine a neurotoxicity ...
Home recording of 3-Hz spike-wave discharges in adults with absence epilepsy using the wearable Sensor Dot KU Leuven
OBJECTIVE: Home monitoring of 3-Hz spike-wave discharges (SWDs) in patients with refractory absence epilepsy could improve clinical care by replacing the inaccurate seizure diary with objective counts. We investigated the use and performance of the Sensor Dot (Byteflies) wearable in persons with absence epilepsy in their home environment. METHODS: Thirteen participants (median age = 22 years, 11 female) were enrolled at the university hospitals ...
Detecting Epileptic Seizures Using Hand-Crafted and Automatically Constructed EEG Features KU Leuven
Epileptic seizure detection aims to replace unreliable seizure diaries by a model that automatically detects seizures based on electroencephalography (EEG) sensors. However, developing such a model is difficult and time consuming as it requires manually searching for relevant features from complex EEG data. Domain experts may have a partial understanding of the EEG characteristics that indicate seizures, but this knowledge is often not ...
CoRe-Sleep: A Multimodal Fusion Framework for Time Series Robust to Imperfect Modalities. KU Leuven
Sleep abnormalities can have severe health consequences. Automated sleep staging, i.e. labelling the sequence of sleep stages from the patient's physiological recordings, could simplify the diagnostic process. Previous work on automated sleep staging has achieved great results, mainly relying on the EEG signal. However, often multiple sources of information are available beyond EEG. This can be particularly beneficial when the EEG recordings are ...
Position Paper From the Digital Twins in Healthcare to the Virtual Human Twin: A Moon-Shot Project for Digital Health Research KU Leuven
The idea of a systematic digital representation of the entire known human pathophysiology, which we could call the Virtual Human Twin, has been around for decades. To date, most research groups focused instead on developing highly specialised, highly focused patient-specific models able to predict specific quantities of clinical relevance. While it has facilitated harvesting the low-hanging fruits, this narrow focus is, in the long run, leaving ...