Head Trauma

Development and validation of an interpretable machine learning model for predicting post-stroke epilepsy.

BACKGROUND: Epilepsy is a serious complication after an ischemic stroke. Although two studies have d...

Commentary on "develop a radiomics-based machine learning model to predict the stone-free rate post-percutaneous nephrolithotomy".

A novel virtual robotic platform for controlling six degrees of freedom assistive devices with body-machine interfaces.

Body-machine interfaces (BoMIs)-systems that control assistive devices (e.g., a robotic manipulator)...

Enhancing post-training evaluation of annual performance agreement training: A fusion of fsQCA and artificial neural network approach.

This study aims to enhance the post-training evaluation of the annual performance agreement (APA) tr...

Robot-aided assessment and associated brain lesions of impaired ankle proprioception in chronic stroke.

BACKGROUND: Impaired ankle proprioception strongly predicts balance dysfunction in chronic stroke. H...

Legal and Ethical Considerations of Artificial Intelligence for Residents in Post-Acute and Long-Term Care.

This article proposes a framework for examining the ethical and legal concerns for using artificial ...

Multivariate modeling and prediction of cerebral physiology in acute traumatic neural injury: A scoping review.

Traumatic brain injury (TBI) poses a significant global public health challenge necessitating a prof...

Deep learning-based automated detection and segmentation of bone and traumatic bone marrow lesions from MRI following an acute ACL tear.

INTRODUCTION: Traumatic bone marrow lesions (BML) are frequently identified on knee MRI scans in pat...

Persistent spiking activity in neuromorphic circuits incorporating post-inhibitory rebound excitation.

. This study introduces a novel approach for integrating the post-inhibitory rebound excitation (PIR...

Prediction of post-delivery hemoglobin levels with machine learning algorithms.

Predicting postpartum hemorrhage (PPH) before delivery is crucial for enhancing patient outcomes, en...

Quantifying social capital creation in post-disaster recovery aid in Indonesia: methodological innovation by an AI-based language model.

Smooth interaction with a disaster-affected community can create and strengthen its social capital, ...

Clinical domain knowledge-derived template improves post hoc AI explanations in pneumothorax classification.

OBJECTIVE: Pneumothorax is an acute thoracic disease caused by abnormal air collection between the l...

Cancer diagnosis in the post-coronavirus disease era: the promising role of telepathology and artificial intelligence.

Enhancing post-traumatic stress disorder patient assessment: leveraging natural language processing for research of domain criteria identification using electronic medical records.

BACKGROUND: Extracting research of domain criteria (RDoC) from high-risk populations like those with...

Classification of short and long term mild traumatic brain injury using computerized eye tracking.

Accurate, and objective diagnosis of brain injury remains challenging. This study evaluated useabili...

Can machine learning predict late seizures after intracerebral hemorrhages? Evidence from real-world data.

INTRODUCTION: Intracerebral hemorrhage represents 15 % of all strokes and it is associated with a hi...

Interdisciplinary approach to identify language markers for post-traumatic stress disorder using machine learning and deep learning.

Post-traumatic stress disorder (PTSD) lacks clear biomarkers in clinical practice. Language as a pot...

Predicting post-surgical functional status in high-grade glioma with resting state fMRI and machine learning.

PURPOSE: High-grade glioma (HGG) is the most common and deadly malignant glioma of the central nervo...

Impact Exploration of Spatiotemporal Feature Derivation and Selection on Machine Learning-Based Predictive Models for Post-Embolization Cerebral Aneurysm Recanalization.

PURPOSE: To enhance the performance of machine learning (ML) models for the post-embolization recana...

Assessing the efficacy of 2D and 3D CNN algorithms in OCT-based glaucoma detection.

Glaucoma is a progressive neurodegenerative disease characterized by the gradual degeneration of ret...

Assessment of image quality and impact of deep learning-based software in non-contrast head CT scans.

In this retrospective study, we aimed to assess the objective and subjective image quality of differ...