Neurology

Head Trauma

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

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Radiogenomic explainable AI with neural ordinary differential equation for identifying post-SRS brain metastasis radionecrosis.

BACKGROUND: Stereotactic radiosurgery (SRS) is widely used for managing brain metastases (BMs), but ...

Robot-Assisted Endodontic Retreatment: A Case Report with Clinical Considerations.

Fiber posts present significant challenges for nonsurgical endodontic retreatment, as improper remov...

Plasma IL-17A is increased in patients with critical MIS-C and associated to in-hospital mortality.

BACKGROUND: Multisystem inflammatory syndrome in children (MIS-C) is a rare and severe post-COVID-19...

Prognosis modelling of adverse events for post-PCI treated AMI patients based on inflammation and nutrition indexes.

OBJECTIVE: This study aimed to evaluate the predictive performance of inflammatory and nutritional i...

Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis.

This study aimed to compare and evaluate the prediction accuracy and risk of bias (ROB) of post-trau...

Towards a decision support system for post bariatric hypoglycaemia: development of forecasting algorithms in unrestricted daily-life conditions.

BACKGROUND: Post bariatric hypoglycaemic (PBH) is a late complication of weight loss surgery, charac...

Automated post-run analysis of arrayed quantitative PCR amplification curves using machine learning.

BACKGROUND: The TaqMan Array Card (TAC) is an arrayed, high-throughput qPCR platform that can simult...

Assessing donor kidney function: the role of CIRBP in predicting delayed graft function post-transplant.

INTRODUCTION: Delayed graft function (DGF) shortens the survival time of transplanted kidneys and in...

Predicting work ability impairment in post COVID-19 patients: a machine learning model based on clinical parameters.

The Post COVID-19 condition (PCC) is a complex disease affecting health and everyday functioning. Th...

Explainable post hoc portfolio management financial policy of a Deep Reinforcement Learning agent.

Financial portfolio management investment policies computed quantitatively by modern portfolio theor...

Working-memory load decoding model inspired by brain cognition based on cross-frequency coupling.

Working memory, a fundamental cognitive function of the brain, necessitates the evaluation of cognit...

Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus.

This study sought to establish and validate an interpretable CT radiomics-based machine learning mod...

Machine learning analysis of cervical balance in early-onset scoliosis post-growing rod surgery: a case-control study.

We aimed to analyze the cervical sagittal alignment change following the growing rod treatment in ea...

AI-based models to predict decompensation on traumatic brain injury patients.

Traumatic Brain Injury (TBI) is a form of brain injury caused by external forces, resulting in tempo...

Changes in hematoma volume following aneurysmal subarachnoid hemorrhage and its impact on patient prognosis.

OBJECTIVE: This study aims to investigate the effects of preoperative intracerebral hematoma volume ...

Rad4XCNN: A new agnostic method for post-hoc global explanation of CNN-derived features by means of Radiomics.

BACKGROUND AND OBJECTIVE: In recent years, machine learning-based clinical decision support systems ...

Survival machine learning methods for mortality prediction after heart transplantation in the contemporary era.

Although prediction models for heart transplantation outcomes have been developed previously, a comp...

Accelerating computational fluid dynamics simulation of post-combustion carbon capture modeling with MeshGraphNets.

Packed columns are commonly used in post-combustion processes to capture CO emissions by providing e...

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