Neurology

Head Trauma

Latest AI and machine learning research in head trauma for healthcare professionals.

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Risk tools for predicting long-term sequelae based on symptom profiles after known and undetected SARS-CoV-2 infections in the population.

The aim was to determine the profile of long-term symptoms after known and undetected SARS-CoV-2 inf...

Construction and validation of a machine learning based prognostic prediction model for children with traumatic brain injury.

OBJECTIVE: This study aimed to establish a prediction model for the short-term prognosis of children...

Investigation of the Significance of Blood Signatures on Sepsis-Induced Acute Lung Injury in Sepsis Within 24 Hours.

Sepsis is an infection-induced dysregulated cellular response that leads to multiorgan dysfunction....

Dynamic Predictive Models of Cardiogenic Shock in STEMI: Focus on Interventional and Critical Care Phases.

: While early risk stratification in STEMI is essential, the threat of cardiogenic shock (CS) persis...

Heat to hypoxia cross-adaptation: Effects of 6-week post-exercise hot-water immersion on exercise performance in acute hypoxia.

Cross-adaptation occurs when exposure to one environmental stressor (e.g., heat) induces protective ...

Temporal wheat proteome remodeling by deoxynivalenol reveals novel detoxification signatures and strategies across cultivars.

Fusarium head blight (FHB) is a globally devastating fungal disease resulting in reduced grain yield...

Using machine learning models to predict post-revascularization thrombosis in PAD.

BACKGROUND: Graft/ stent thrombosis after lower extremity revascularization (LER) is a serious compl...

CLEAR-Shock: Contrastive LEARning for Shock.

Shock is a life-threatening condition characterized by generalized circulatory failure, which can ha...

Machine learning models for acute kidney injury prediction and management: a scoping review of externally validated studies.

Despite advancements in medical care, acute kidney injury (AKI) remains a major contributor to adver...

Leveraging AI to explore structural contexts of post-translational modifications in drug binding.

Post-translational modifications (PTMs) play a crucial role in allowing cells to expand the function...

Interpretable machine learning model for predicting post-hepatectomy liver failure in hepatocellular carcinoma.

Post-hepatectomy liver failure (PHLF) is a severe complication following liver surgery. We aimed to ...

Development and external validation of a model for post-endoscopic retrograde cholangiopancreatography pancreatitis.

Post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is a common complicati...

Using machine learning involving diagnoses and medications as a risk prediction tool for post-acute sequelae of COVID-19 (PASC) in primary care.

BACKGROUND: The aim of our study was to determine whether the application of machine learning could ...

Brain circuits that regulate social behavior.

Social interactions are essential for the survival of individuals and the reproduction of population...

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