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Magnetic resonance imaging (MRI) is a cornerstone of non-invasive diagnostics and treatment monitoring, particularly for diseases of the central nervous system. Although 1.5- and 3 Tesla (T) field strengths remain the clinical standard, the advent of 7 T MRI represents a transformative step forward, offering superior spatial resolution, contrast, and sensitivity for visualizing neuroanatomy, metabolism, and function.

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Osteoarthritis (OA) of the knee is the most common joint disease, characterized by the degeneration of joint cartilage. Intra-articular hyaluronic acid (IAHA) injections are a well-established non-surgical treatment. This retrospective study analyzed knee OA patients receiving IAHA combined with niacinamide injections, assessing pain reduction in relation to patient data, the number of injections, and radiological findings.

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Background: The accuracy of Logical Observation Identifiers Names and Codes (LOINC) mappings is reportedly low, and the LOINC codes used for research purposes in Korea have not been validated for accuracy or usability. Our study aimed to evaluate the discrepancies and similarities in interoperability using existing LOINC mappings in actual patient care settings.

Methods: We collected data on local test codes and their corresponding LOINC mappings from seven university hospitals.

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  • Elevated levels of activated complement proteins in cerebrospinal fluid (CSF) are linked to increased severity of multiple sclerosis (MS) and correlate with brain imaging and disease biomarkers.
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Dense Paraphrasing for multimodal dialogue interpretation.

Front Artif Intell

December 2024

Computer Science Department, Brandeis University, Waltham, MA, United States.

Multimodal dialogue involving multiple participants presents complex computational challenges, primarily due to the rich interplay of diverse communicative modalities including speech, gesture, action, and gaze. These modalities interact in complex ways that traditional dialogue systems often struggle to accurately track and interpret. To address these challenges, we extend the textual enrichment strategy of Dense Paraphrasing (DP), by translating each nonverbal modality into linguistic expressions.

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