AIMC Topic: Fibrinogen
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Human protein interaction networks of ancestral and variant SARS-CoV-2 in organ-specific cells and bodily fluids.
Nature communications
Jul 1, 2025
Understanding SARS-CoV-2 human protein-protein interactions (PPIs) and the host response to infection is essential for developing effective COVID-19 antivirals. However, how the ancestral virus and its variants remodel virus-host protein assemblies i...
Association between fibrinogen levels and prognosis in critically bleeding patients: exploration of the optimal therapeutic threshold.
European journal of trauma and emergency surgery : official publication of the European Trauma Society
May 23, 2025
BACKGROUND: Severe bleeding is a leading cause of ICU admission and mortality. Fibrinogen plays a crucial role in prognosis, yet optimal thresholds and supplementation targets remain unclear.
3D Bioprinting and Artificial Intelligence-Assisted Biofabrication of Personalized Oral Soft Tissue Constructs.
Advanced healthcare materials
Dec 17, 2024
Regeneration of oral soft tissue defects, including mucogingival defects associated with the recession or loss of gingival and/or mucosal tissues around teeth and implants, is crucial for restoring oral tissue form, function, and health. This study p...
Can machine learning provide preoperative predictions of biological hemostasis after extracorporeal circulation for cardiac surgery?
The Journal of thoracic and cardiovascular surgery
Nov 4, 2023
OBJECTIVES: The goal of this study was to improve decision making regarding the transfusion of patients at the end of extracorporeal circulation for cardiac surgery through machine learning predictions of the evolution of platelets counts, prothrombi...
Space-time-regulated imaging analyzer for smart coagulation diagnosis.
Cell reports. Medicine
Oct 6, 2022
The development of intelligent blood coagulation diagnoses is awaited to meet the current need for large clinical time-sensitive caseloads due to its efficient and automated diagnoses. Herein, a method is reported and validated to realize it through ...
Application of supervised machine learning algorithms to predict the risk of hidden blood loss during the perioperative period in thoracolumbar burst fracture patients complicated with neurological compromise.
Frontiers in public health
Sep 26, 2022
BACKGROUND: Machine learning (ML) is a type of artificial intelligence (AI) and has been utilized in clinical research and practice to construct high-performing prediction models. Hidden blood loss (HBL) is prevalent during the perioperative period o...
Application of Machine Learning to Assess Interindividual Variability in Rapid-Acting Insulin Responses After Subcutaneous Injection in People With Type 1 Diabetes.
Canadian journal of diabetes
Sep 6, 2021
OBJECTIVES: Circulating insulin concentrations mediate vascular-inflammatory and prothrombotic factors. However, it is unknown whether interindividual differences in circulating insulin levels are associated with different inflammatory and prothrombo...
The Use of Machine Learning Techniques to Determine the Predictive Value of Inflammatory Biomarkers in the Development of Type 2 Diabetes Mellitus.
Metabolic syndrome and related disorders
Feb 16, 2021
Certain inflammatory biomarkers, such as interleukin-6, interleukin-1, C-reactive protein (CRP), and fibrinogen, are prototypical acute-phase parameters that can also be predictors of cardiovascular disease. However, this inflammatory response can a...
Evaluation of the Classification Accuracy of the Kidney Biopsy Direct Immunofluorescence through Convolutional Neural Networks.
Clinical journal of the American Society of Nephrology : CJASN
Sep 16, 2020
BACKGROUND AND OBJECTIVES: Immunohistopathology is an essential technique in the diagnostic workflow of a kidney biopsy. Deep learning is an effective tool in the elaboration of medical imaging. We wanted to evaluate the role of a convolutional neura...
Biopsy
Fibrinogen
Immunoglobulins
Complement C3
Neural Networks, Computer
Fluorescent Antibody Technique, Direct
Female
Complement C1q
Aged
Immunoglobulin kappa-Chains
Humans
Adult
Image Processing, Computer-Assisted
Male
Kidney
Middle Aged
Kidney Diseases
Immunoglobulin lambda-Chains
ROC Curve
Area Under Curve
Quantitative design rules for protein-resistant surface coatings using machine learning.
Scientific reports
Jan 22, 2019
Preventing biological contamination (biofouling) is key to successful development of novel surface and nanoparticle-based technologies in the manufacturing industry and biomedicine. Protein adsorption is a crucial mediator of the interactions at the ...
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