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A robust multimodal brain MRI-based diagnostic model for migraine: validation across different migraine phases and longitudinal follow-up data.
J Headache Pain
January 2025
Department of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
Inter-individual variability in symptoms and the dynamic nature of brain pathophysiology present significant challenges in constructing a robust diagnostic model for migraine. In this study, we aimed to integrate different types of magnetic resonance imaging (MRI), providing structural and functional information, and develop a robust machine learning model that classifies migraine patients from healthy controls by testing multiple combinations of hyperparameters to ensure stability across different migraine phases and longitudinally repeated data. Specifically, we constructed a diagnostic model to classify patients with episodic migraine from healthy controls, and validated its performance across ictal and interictal phases, as well as in a longitudinal setting.
View Article and Find Full Text PDFResistive memory-based zero-shot liquid state machine for multimodal event data learning.
Nat Comput Sci
January 2025
Key Lab of Fabrication Technologies for Integrated Circuits and Key Laboratory of Microelectronic Devices and Integrated Technology, Institute of Microelectronics of the Chinese Academy of Sciences, Beijing, China.
The human brain is a complex spiking neural network (SNN) capable of learning multimodal signals in a zero-shot manner by generalizing existing knowledge. Remarkably, it maintains minimal power consumption through event-based signal propagation. However, replicating the human brain in neuromorphic hardware presents both hardware and software challenges.
View Article and Find Full Text PDFDeep learning model for automatic detection of different types of microaneurysms in diabetic retinopathy.
Eye (Lond)
January 2025
Department of Surgical Sciences, University of Turin, Turin, Italy.
Purpose: This study aims to develop a deep-learning-based software capable of detecting and differentiating microaneurysms (MAs) as hyporeflective or hyperreflective on structural optical coherence tomography (OCT) images in patients with non-proliferative diabetic retinopathy (NPDR).
Methods: A retrospective cohort of 249 patients (498 eyes) diagnosed with NPDR was analysed. Structural OCT scans were obtained using the Heidelberg Spectralis HRA + OCT device.
The blood pressure lowering effect of beetroot juice is impaired in periodontitis and recovered after periodontal treatment.
NPJ Biofilms Microbiomes
January 2025
Department of Health and Genomics, FISABIO Foundation, Valencia, Spain.
We have previously demonstrated that subgingival levels of nitrate-reducing bacteria, as well as the in vitro salivary nitrate reduction capacity (NRC), were diminished in periodontitis patients, increasing after periodontal treatment. However, it remains unclear if an impaired NRC in periodontitis can affect systemic health. To determine this, the effect of nitrate-rich beetroot juice (BRJ) on blood pressure was determined in 15 periodontitis patients before and 70 days after periodontal treatment (i.
View Article and Find Full Text PDFPerformance evaluation of a machine learning-based methodology using dynamical features to detect nonwear intervals in actigraphy data in a free-living setting.
Sleep Health
January 2025
Department of Human and Development and Family Studies, Pennsylvania State University, University Park, Pennsylvania, USA.
Goal And Aims: One challenge using wearable sensors is nonwear time. Without a nonwear (e.g.
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