Neurology

Head Trauma

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

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Elevated Levels of Urinary Biomarkers TIMP-2 and IGFBP-7 Predict Acute Kidney Injury in Neonates after Congenital Heart Surgery.

 This article investigated the utility of urine biomarkers tissue inhibitor of metalloproteinase-2 ...

Evaluation of Unfractionated Heparin Dosing by Antifactor Xa During Targeted Temperature Management Post Cardiac Arrest.

PURPOSE: To evaluate unfractionated heparin (UFH) dosing guided by antifactor Xa levels during targe...

The effect of a post-scan processing denoising system on image quality and morphometric analysis.

PURPOSE: MR image quality and subsequent brain morphometric analysis are inevitably affected by nois...

Assessing the utility of low resolution brain imaging: treatment of infant hydrocephalus.

As low-field MRI technology is being disseminated into clinical settings around the world, it is imp...

DNA methylation-based classification of malformations of cortical development in the human brain.

Malformations of cortical development (MCD) comprise a broad spectrum of structural brain lesions fr...

Post-script-Retail forecasting: Research and practice.

This note updates the 2019 review article "Retail forecasting: Research and practice" in the context...

Unraveling somatotopic organization in the human brain using machine learning and adaptive supervoxel-based parcellations.

In addition to the well-established somatotopy in the pre- and post-central gyrus, there is now stro...

A Bidirectional Interpolation Method for Post-Processing in Sampling-Based Robot Path Planning.

This paper proposes a post-processing method called bidirectional interpolation method for sampling-...

Robotic repair of post-oesophagectomy hiatal hernia.

Diaphragmatic hiatal hernia is a potential complication of oesophagectomy in cancer patients. Over t...

Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies.

Interstitial fibrosis, tubular atrophy, and inflammation are major contributors to kidney allograft ...

Deep learning-based thin-section MRI reconstruction improves tumour detection and delineation in pre- and post-treatment pituitary adenoma.

Even a tiny functioning pituitary adenoma could cause symptoms; hence, accurate diagnosis and treatm...

Quantifying the Impacts of Pre- and Post-Conception TSH Levels on Birth Outcomes: An Examination of Different Machine Learning Models.

BACKGROUND: While previous studies identified risk factors for diverse pregnancy outcomes, tradition...

Automated post-operative brain tumour segmentation: A deep learning model based on transfer learning from pre-operative images.

Automated brain tumour segmentation from post-operative images is a clinically relevant yet challeng...

Deceptive Online Content Detection Using Only Message Characteristics and a Machine Learning Trained Expert System.

This paper considers the use of a post metadata-based approach to identifying intentionally deceptiv...

Brain oscillatory correlates of visuomotor adaptive learning.

Sensorimotor adaptation involves the recalibration of the mapping between motor command and sensory ...

Post-reconstruction attenuation correction for SPECT myocardium perfusion imaging facilitated by deep learning-based attenuation map generation.

BACKGROUND: Attenuation correction can improve the quantitative accuracy of single-photon emission c...

Evaluating Performance of EEG Data-Driven Machine Learning for Traumatic Brain Injury Classification.

OBJECTIVES: Big data analytics can potentially benefit the assessment and management of complex neur...

Non-transfer Deep Learning of Optical Coherence Tomography for Post-hoc Explanation of Macular Disease Classification.

Deep transfer learning is a popular choice for classifying monochromatic medical images using models...

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