AIMC Topic: Hemodynamics

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Development and Validation of an Interpretable Hemodynamics-Based Machine Learning Model for Predicting Cerebral Arteriovenous Malformation Rupture.

Translational stroke research
Cerebral arteriovenous malformation (AVM) is a cerebrovascular disease associated with a risk of intracranial hemorrhage. Currently, most risk prediction models for AVM rupture are based on demographic characteristics and lesion morphology, while qua...

Ultrasound as the New Stethoscope: A Journey From Just Locating Fluid to Assessing Haemodynamics and Venous Congestion.

British journal of hospital medicine (London, England : 2005)
Point-of-care ultrasound (POCUS) has evolved from a simple tool for fluid localization to a comprehensive modality for hemodynamic assessment and real-time clinical decision-making. The Bedside Lung Ultrasound in Emergency (BLUE) protocol enables cli...

Hemodynamic determinants of postoperative neurocognitive impairment using Random Forest analysis and partial dependence plots.

Scientific reports
This study investigated the effect of hemodynamic data during cardiopulmonary bypass (CPB) on neurocognitive impairment in patients undergoing coronary artery bypass graft (CABG) surgery using machine learning algorithms. Twenty-eight CABG patients w...

Correspondence regarding "Clinical parameters-based machine learning models for predicting intraoperative hemodynamic instability in hypertensive pheochromocytomas and paragangliomas patients".

World journal of urology
Zhao et al. present machine-learning models to predict intraoperative hemodynamic instability in hypertensive pheochromocytoma and paraganglioma surgery. The clinical motivation is sound and the reported discrimination and decision-curve metrics indi...

Clinical parameters-based machine learning models for predicting intraoperative hemodynamic instability in hypertensive pheochromocytomas and paragangliomas patients.

World journal of urology
PURPOSE: To create machine learning (ML) models based on inflammatory markers and coagulation parameters for predicting intraoperative hemodynamic Instability (HI) in sustained hypertensive patients with pheochromocytomas and paragangliomas (PPGLs).

AI-powered automated model construction for patient-specific CFD simulations of aortic flows.

Science advances
Image-based modeling is essential for understanding cardiovascular hemodynamics and advancing the diagnosis and treatment of cardiovascular diseases. Constructing patient-specific vascular models remains labor-intensive, error-prone, and time-consumi...

Perioperative Quality Initiative consensus statement on goal-directed haemodynamic therapy.

British journal of anaesthesia
Perioperative goal-directed haemodynamic therapy (GDHT) includes a variety of protocolised approaches to the assessment and management of the circulatory system and blood flow for patients undergoing surgery. Here we present updated consensus stateme...

Predictive modeling and machine learning show poor performance of clinical, morphological, and hemodynamic parameters for small intracranial aneurysm rupture.

Scientific reports
Small intracranial aneurysms (SIAs) (< 5 mm) are increasingly detected due to advanced imaging, but predicting rupture risk remains challenging. Rupture, though rare, can cause devastating subarachnoid hemorrhage. This study analyzed 141 SIAs (101 un...

Multimodal nomogram integrating deep learning radiomics and hemodynamic parameters for early prediction of post-craniotomy intracranial hypertension.

Scientific reports
To evaluate the effectiveness of deep learning radiomics nomogram in distinguishing early intracranial hypertension (IH) following primary decompressive craniectomy (DC) in patients with severe traumatic brain injury (TBI) and to demonstrate its pote...

Evaluating artificial intelligence models for rupture risk prediction in unruptured intracranial aneurysms: a focus on vessel geometry and hemodynamic insights.

Neurosurgical review
The estimation of rupture risk in Unruptured Intracranial Aneurysm (UIA) constitutes a major area of clinical interest due to the significant morbidity and mortality rates associated with aneurysm rupture. Classic clinical models based on factors suc...