Academic Articles & Research Papers

Amplified MS2 labeling reveals heterogeneous dynamics of RNA granules in the live murine brain ex vivo.

A paradigm shift toward explainable and federated intelligence for brain tumor MRI analysis.

Cyclic multiplex fluorescent immunohistochemistry and machine learning reveal distinct states of astrocytes and microglia in normal aging and Alzheimer’s disease

Abstract Background Astrocytes and microglia react to Aβ plaques, neurofibrillary tangles, and neurodegeneration in the Alzheimer’s disease (AD) brain. Single-nuclei and single-cell RNA-seq have revealed multiple states or subpopulations of...

Deep Learning-Based Approaches for Brain Tumour Segmentation and Classification

Brain tumours are caused by the abnormal growth of cells in the brain. This occurs mainly due to genetic changes or exposure to X-ray radiation. When the tumours are detected early, they can be removed via surgery. The tumour can be removed...

Epigenetic dysregulation of high-grade gliomas: from heterogeneity to brain network modulation.

Immunogenic cell death-related macrophage gene model for prognostic prediction in glioblastoma

Abstract Glioblastoma (GBM) is an extremely aggressive and diverse type of brain tumor that is associated with a poor prognosis. Immunogenic cell death (ICD) is a particular form of cellular demise that is closely linked to antineoplastic i...

Customizing skills for assistive robotic manipulators, an inverse reinforcement learning approach with error-related potentials

Teaching an assistive robotic manipulator to move objects in a cluttered table requires demonstrations from expert operators, but what if the experts are individuals with motor disabilities? Batzianoulis et al. propose a learning approach w...

Generative-Adversarial-Network-Based Image Reconstruction for the Capacitively Coupled Electrical Impedance Tomography of Stroke

This study investigated the potential of machine-learning-based stroke image reconstruction in capacitively coupled electrical impedance tomography. The quality of brain images reconstructed using the adversarial neural network (cGAN) was e...

Optimizing brain functional-structural architecture with cTBS to reduce relapse in alcohol use disorder: a randomized controlled trial.

Improving Parameter Recovery in Computational Models: Employing Outlier-Insensitive Loss Functions.

Brain network-based stratification of mental health disorders: design and cohort description of the STRATIFY and ESTRA studies.

Guiding functional near-infrared spectroscopy research on sedentary behavior and brain health.

Gut Microbiota and Targeted Biomarkers Analysis in Patients With Cognitive Impairment

Gut microbial alteration is closely associated with brain disorders including cognitive impairment (CI). Gut microbes have the potential to predicate the development of diseases. However, the gut microbial markers for CI remain to be elucid...

Deep Learning-Based Visual Complexity Analysis of Electroencephalography Time-Frequency Images: Can It Localize the Epileptogenic Zone in the Brain?

In drug-resistant epilepsy, a visual inspection of intracranial electroencephalography (iEEG) signals is often needed to localize the epileptogenic zone (EZ) and guide neurosurgery. The visual assessment of iEEG time-frequency (TF) images i...

Precise diagnosis of Alzheimer’s disease based on sex-specific gray matter characteristics

IntroductionThere are notable sex differences in the gray matter of Alzheimer’s disease(AD) patients’ brains, but current evidence is insufficient to prove these differences aid diagnosis effectively.MethodsMultivariate analysis of variance...

Integrated Causal Learning Workflow of Brain Iron Deposition in Patients with PD based on QSM.

Neural Networks for Machine Learning

In order for a digital neocortex to learn a new skill, it will still require many iterations of education, just as a biological neocortex does, but once a single neocortex somewhere and at some time learns something, it can share that knowl...

Exploring the application and challenges of fNIRS technology in early detection of Parkinson’s disease

BackgroundParkinson’s disease (PD) is a prevalent neurodegenerative disorder that significantly benefits from early diagnosis for effective disease management and intervention. Despite advancements in medical technology, there remains a cri...

Application of MRI-Based Radiomics in Preoperative Prediction of NF2 Alteration in Intracranial Meningiomas

PurposeThis study aimed to investigate the feasibility of predicting NF2 mutation status based on the MR radiomic analysis in patients with intracranial meningioma.MethodsThis retrospective study included 105 patients with meningiomas, incl...

Diffusion MRI processing in the HEALthy Brain and Child Development study: Innovations and applications.