Head Trauma

Automatic delineation of cervical cancer target volumes in small samples based on multi-decoder and semi-supervised learning and clinical application.

Radiotherapy has been demonstrated to be one of the most significant treatments for cervical cancer,...

The infection post flexible UreteroreNoscopy (I-FUN) predictive model based on machine learning: a new clinical tool to assess the risk of sepsis post retrograde intrarenal surgery for kidney stone disease.

PURPOSE: To create a machine-learning model for estimating the likelihood of post-retrograde intrare...

Active Machine Learning for Pre-procedural Prediction of Time-Varying Boundary Condition After Fontan Procedure Using Generative Adversarial Networks.

The Fontan procedure is the definitive palliation for pediatric patients born with single ventricles...

Beyond MELD Score: Association of Machine Learning-derived CT Body Composition with 90-Day Mortality Post Transjugular Intrahepatic Portosystemic Shunt Placement.

PURPOSE: To determine the association of machine learning-derived CT body composition and 90-day mor...

Post-Cardiac arrest outcome prediction using machine learning: A systematic review and meta-analysis.

BACKGROUND: Early and reliable prognostication in post-cardiac arrest patients remains challenging, ...

Machine learning-based assessment of regional-scale variation of landslide susceptibility in central Vietnam.

Recurrent landslide events triggered by typhoons and tropical storms over Vietnam pose a longstandin...

A new approach to assess post-mortem interval: A machine learning-assisted label-free ATR-FTIR analysis of human vitreous humor.

A crucial issue in forensics is determining the post-mortem interval (PMI), the time between death a...

Artificial intelligence-driven pharmaceutical industry: A paradigm shift in drug discovery, formulation development, manufacturing, quality control, and post-market surveillance.

The advent of artificial intelligence (AI) has catalyzed a profound transformation in the pharmaceut...

A Multicenter Cohort Study on Ultrasound-based Deep Learning Nomogram for Predicting Post-Neoadjuvant Chemotherapy Axillary Lymph Node Status in Breast Cancer Patients.

RATIONALE AND OBJECTIVES: The aim of this study was to evaluate the capability of an ultrasound (US)...

One-year employment outcome prediction after traumatic brain injury: A CENTER-TBI study.

BACKGROUND: Traumatic brain injury (TBI) can come with long term consequences for functional outcome...

A novel mean shape based post-processing method for enhancing deep learning lower-limb muscle segmentation accuracy.

This study aims at improving the lower-limb muscle segmentation accuracy of deep learning approaches...

Machine-learning-based models for the optimization of post-cervical spinal laminoplasty outpatient follow-up schedules.

BACKGROUND: Patients undergo regular clinical follow-up after laminoplasty for cervical myelopathy. ...

Machine learning for post-liver transplant survival: Bridging the gap for long-term outcomes through temporal variation features.

BACKGROUND: The long-term survival of liver transplant (LT) recipients is essential for optimizing o...

Paying attention to uncertainty: A stochastic multimodal transformers for post-traumatic stress disorder detection using video.

BACKGROUND AND OBJECTIVES: Post-traumatic stress disorder is a debilitating psychological condition ...

Machine Learning Based Prediction of Imminent ICP Insults During Neurocritical Care of Traumatic Brain Injury.

BACKGROUND: In neurointensive care, increased intracranial pressure (ICP) is a feared secondary brai...

Predicting Outcomes of Preterm Neonates Post Intraventricular Hemorrhage.

Intraventricular hemorrhage (IVH) in preterm neonates presents a high risk for developing posthemorr...

Effect of ethanol extract of nigella sativa L seeds and propofol on BDNF protein level as neuroplasticity and neuroprotection of traumatic brain injury in rats.

BACKGROUND: Traumatic brain injury (TBI) is a change in brain function or evidence of brain patholog...

Exploration of fractional flow reservation score based on artificial intelligence post-processing for coronary artery lesions in patients with diabetes and coronary heart disease.

In order to evaluate the relationship between coronary heart disease (CHD) and fractional flow reser...

Evaluation and analysis of risk factors for adverse events of the fractured vertebra post-percutaneous kyphoplasty: a retrospective cohort study using multiple machine learning models.

BACKGROUND: Adverse events of the fractured vertebra (AEFV) post-percutaneous kyphoplasty (PKP) can ...

Adaptive Machine Learning Systems in Medicine: The Post-Authorization Phase.

Regional and National Trends in Tuberculosis Research in South Asian Association for Regional Cooperation Countries: Post-COVID-19 Pandemic Machine Learning Factorial Analysis.

BACKGROUND: The number of tuberculosis (TB)-related morbidities and mortalities is still high in the...