259594 research outputs found
Sort by
Comparison of lower body joint kinematics during change of direction tasks estimated using a markerless and a markerbased method
No full textMarker-based (MB) motion capture systems face challenges like marker loss, soft tissue artifacts, and manual processing. Markerless (ML) motion capture systems might be particularly advantageous for capturing dynamic, non-linear movements like change of direction (COD) movements. The agreement between MB and ML systems for lower extremity joint kinematics during COD tasks was evaluated. Nineteen athletes performed cutting movements in 5 directions at 3 intensities. Data was captured using infrared and video cameras. Joint angles were computed, and the agreement was assessed using prediction band and extended Bland-Altman (BA) methods. Knee joint angles showed the smallest random and systematic errors (bias = 4.34°, area = 3102.57 deg·stance%; BA: bias = 3.34°, limits of agreement (LoA) = ± 11.38°) compared to ankle and hip joint angles. Flexion/extension angles displayed a smaller random error (area = 2919.74 deg·stance%; LoA = ± 10.71°) compared to ab-/adduction (area = 3477.70 deg·stance%; LoA ± 12.16°) and internal/external rotation angles (area = 4630.68 deg·stance%; LoA = ± 15.75°). Slower and straight-line movements demonstrated stronger agreement than sharper, non-linear directions. These findings provide valuable insight for researchers and practitioners when placing ML data in the context of existing data, with particular care when considering highly dynamic, non-linear movements or internal/external rotation angles
Cerebral amyloid angiopathy in spontaneous intracerebral hemorrhage – radiology and immunohistochemistry in a consecutive surgical series
No full textIntroductionCerebral amyloid angiopathy (CAA) is a major cause of spontaneous intracerebral hemorrhage (ICH) in elderly patients and is associated with a high risk of recurrent hemorrhagic events.Research questionWhether the likelihood of CAA can be estimated using radiological criteria such as the Edinburgh criteria.Material and methodsWe conducted a retrospective analysis of consecutive patients with spontaneous ICH who underwent neurosurgical hematoma evacuation between 01/2023 and 02/2025. Baseline clinical characteristics, radiological findings, and histopathological evaluations were assessed. Patients were classified as CAA-positive or CAA-negative based on immunohistochemical staining for amyloid-β deposition from intraoperative biopsies.Results53 patients met the inclusion criteria and CAA-positive patients were significantly older (76.9 vs. 65.4 years, p Discussion and conclusionsHistopathologically confirmed CAA is associated with distinct radiological features, including ICH volume, irregular ICH borders and concurrent subarachnoid hemorrhage. Our findings highlight the importance of integrating histopathological analysis to improve diagnostic accuracy, as radiological criteria alone could not definitivey diagnose CAA in all patients
Zwischen Naturgefahr und öffentlicher Wahrnehmung: Analyse der BNN-Berichterstattung zu Starkregenfolgen im Murgtal (2006-2025) mit GIS- und R-gestützten Methoden
No full textEinfluss von Expositionsdauer, Jahreszeit und Blattseneszenz auf die Hitzetoleranz von Picea abies, Abies alba und Fagus sylvatica
No full textStreamlining ophthalmic documentation with anonymized, fine-tuned language models: feasibility study
No full textBackground: The growing administrative burden on clinicians, particularly in medical documentation, contributes to burnout and may compromise patient safety. Recent advancements in generative artificial intelligence (AI) offer a promising solution to improve documentation processes and address these challenges.Objective: This study aims to evaluate the feasibility of using a fine-tuned OpenAI Curie model to automate the generation of medical report summaries (epicrises) in ophthalmology. By assessing the model’s performance through human and automated evaluations, this study seeks to determine its potential for reducing clinician workload while ensuring accuracy, usefulness, and compliance with regulatory requirements.Methods: A data set of around 60,000 anonymized medical letters was created using a custom algorithm to comply with General Data Protection Regulation guidelines. The Curie model was fine-tuned on this data set to generate epicrises from medical histories, diagnoses, and findings. The performance evaluation involved various human assessments and automated evaluations from 2 large language models (LLMs). Results: In the clinical context, 49.9% (384/769) of epicrises were evaluated as helpful or excellent, whereas only 25% (194/769) were considered disturbing. In a human (manual) evaluation, formal correctness was rated significantly higher than the neutral midpoint of 2.5 on the 4-point rating scale, as determined by a 1-sample Wilcoxon signed-rank test (mean 3.59, SD 0.85; W=1686; PConclusions: Our study demonstrates the technical and practical feasibility of introducing fine-tuned commercial LLMs into clinical practice. The AI-generated epicrises were formally and clinically correct in many cases and showed time-saving potential. While medical accuracy and usefulness varied across cases and should be focused on in further developments, a significant workload reduction is likely. Our anonymization process showed that regulatory challenges in the context of AI with patient data can effectively be dealt with. In summary, this study highlights the promise of transformer-based LLMs in reducing administrative tasks in health care. It outlines a pipeline for integrating LLMs into European Union clinical practice, emphasizing the need for careful implementation to ensure efficiency and patient safet
Chronic ethanol exposure induces early epithelial-to-mesenchymal transition (EMT) and premalignant changes in gingival keratinocytes: an in vitro model of very early oral carcinogenesis
No full textEarly molecular events underlying ethanol-induced oral squamous cell carcinoma development remain insufficiently understood, primarily due to a lack of suitable in vitro systems that recapitulate the initial stages of premalignant transformation. Therefore, a cell culture model of human gingival keratinocytes representing progressive stages of early ethanol-induced cell transformation was established and comprehensively characterized. The three cell lines, named “gingival keratinocytes” (GK), “epithelioid” (EPI) and “fibroblastoid” (FIB), and their derivatives were analyzed by morphological, cell biological and biochemical methods, with an emphasis on epithelial-to-mesenchymal transition (EMT)-related signaling pathways. All cell lines were non-tumorigenic in vitro. Chronic ethanol exposure induced distinct morphological and molecular alterations that capture early premalignant changes in vitro. This includes reduced E-Cadherin and enhanced Vimentin expression, accompanied by an increased production of reactive oxygen species. Notably, even morphologically stable cell lines displayed metabolic susceptibility to EMT induction, indicating the early activation of transformation-associated signaling cascades even in a premalignant state. These alterations, however, closely mirrored pathohistological features of oral squamous cell carcinomas such as loss of epithelial integrity and acquisition of mesenchymal characteristics. Collectively, the presented model provides a robust and accessible in vitro platform for investigating very early ethanol-induced oral carcinogenesis mechanisms that are relevant in a premalignant state and may facilitate the identification of diagnostic and preventive biomarkers to improve patient outcomes in alcohol-associated oral cancer and precursor lesions
