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Characterization of cognitive decline in long-duration type 1 diabetes by cognitive, neuroimaging and pathological examinations.
JCI Insight
January 2025
Dianne Hoppes Nunnally Laboratory Research Division, Joslin Diabetes Center, Boston, United States of America.
Background: We aimed to characterize factors associated with the under-studied complication of cognitive decline in aging people with long-duration type 1 diabetes (T1D).
Methods: Joslin "Medalists" (n = 222; T1D ≥ 50 years) underwent cognitive testing. Medalists (n = 52) and age-matched non-diabetic controls (n = 20) underwent neuro- and retinal imaging.
Revised Process for ACNS Guidelines Development.
J Clin Neurophysiol
February 2025
Division of Child Neurology, Department of Neurology, Stanford University, Palo Alto, California, U.S.A.
The development of clinical practice guidelines is an evolving field. In response to the need for consistent, evidence-based medical practice, the American Clinical Neurophysiology Society identified the need to update the Society's guideline development process. The American Clinical Neurophysiology Society Guidelines Committee created an action plan with the goal of improving transparency and rigor for future guidelines and bringing existing guidelines to current standards.
View Article and Find Full Text PDFIntracranial Outcomes of Ipilimumab and Nivolumab in Melanoma Brain Metastases After Progression on Anti-PD-1 Therapy.
JAMA Oncol
January 2025
Department of Medicine, Memorial Sloan Kettering Cancer Center, New York City, New York.
Cross-cultural validity of the Five-Factor Personality Inventory for ICD-11 across nine countries and validation of a French translation.
Personal Disord
January 2025
Laboratoire sur les Interactions Cognition, Action, Émotion (LICAE), UFR STAPS, Universite Paris-Nanterre.
This study aimed to assess measurement invariance for the Five-Factor Inventory for (Oltmanns & Widiger, 2020) across nine national samples from four continents ( = 6,342), and to validate a French translation in seven French-speaking national samples. All were convenience samples of adults. Exploratory factor analyses supported a four-factor structure in the French-speaking Western samples (Belgium, Canada, France, and Switzerland) while a three-factor structure was preferred in the French-speaking African samples (Burkina Faso and Togo), and no adequate structure was found in the Indian sample.
View Article and Find Full Text PDFGraph convolution network-based eeg signal analysis: a review.
Med Biol Eng Comput
January 2025
School of Control Science and Engineering, Tiangong University, Tianjin, 300387, China.
With the advancement of artificial intelligence technology, more and more effective methods are being used to identify and classify Electroencephalography (EEG) signals to address challenges in healthcare and brain-computer interface fields. The applications and major achievements of Graph Convolution Network (GCN) techniques in EEG signal analysis are reviewed in this paper. Through an exhaustive search of the published literature, a module-by-module discussion is carried out for the first time to address the current research status of GCN.
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