Skip to content
Log in
Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

K. Takabayashi

View on Semantic Scholar

4 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Open access 2026

Associating a Polygenic Risk Score for Multiple Sclerosis with Brain MRI Metrics and Cognitive Performance in Healthy UK Biobank Participants.

PURPOSE Multiple sclerosis (MS) is a demyelinating disease of the central nervous system influenced by both genetic and environmental factors. Although a polygenic risk score for MS (MS-PRS) is associated with disease susceptibility, its relationship with white matter (WM) microstructure and cognition in neurologically...

Chen-Yue Feng, J. Kikuta, A. Hagiwara et al. · 0 citations
Open access Aug 2026

Distinct cognitive and structural correlates of pain extent and central sensitization symptoms in older women and men with chronic pain

Chronic pain in later life may be accompanied by alterations in brain structure and cognition, but whether pain extent and central sensitization symptoms identify distinct brain-behavior patterns remains unclear. We examined associations of pain extent and central sensitization symptoms, assessed using the 9-item Centr...

Keiko Yamada, H. Tabata, K. Takabayashi et al. · 0 citations
#diffusion models Sep 2026

DTI-Guided Volumetric Spherical Harmonics Regression for Single-to-Multi-Shell dMRI Synthesis

Multi-shell diffusion MRI (dMRI) unlocks more expressive microstructural modeling than single-shell scans, yet its longer acquisition time hinders deployment in large-scale cohorts and time-constrained clinical settings. Synthesizing an unobserved shell from a single-shell input is fundamentally ill-posed and further c...

Binghua Li, C. Andica, Tong Liang et al. · 0 citations
Open access 2026

Brain Amyloid Burden Mapping Using MR Fingerprinting Aided by Deep Learning.

PURPOSE To develop and externally validate a non-invasive framework for quantifying brain amyloid-β (Aβ) deposition using magnetic resonance fingerprinting (MRF) and neural network-based decoding, with positron emission tomography (PET) as the reference standard. METHODS This prospective multi-site study included 44...

Shohei Fujita, Y. Fushimi, Y. Otsuka et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.