Neurology

Head Trauma

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

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Machine Learning-Driven Decision-Support System for Nursing Risk Assessment in Post-Discharge Care: A Design Science Approach

Hospital readmissions represent a persistent challenge for healthcare systems, often stemming from inadequate post-discharge monitoring. This study presents a Machine Learning (ML)-driven Clinical Decision Support System (CDSS) designed to enhance nursing risk assessment in post-discharge care. Developed using a Design Science Research Methodology, the artefact integrates a digital questionnaire, ...

Machine learning to phenotype pain and predict response to pain interventions among young adults with irritable bowel syndrome

Irritable bowel syndrome (IBS) is a prevalent disorder whose most debilitating symptom is pain. The complex, multifactorial nature of IBS pain leads to highly variable and often inadequate responses to self-management, underscoring the urgent need for personalized prediction models. This ancillary analysis of a randomized controlled trial (NCT03332537) utilized data from 80 young adults with IBS. ...

Mining medical narratives on geriatric falls to predict post-fall hospitalization via survival models and large language models

Timely admission to the emergency department is a crucial determinant of patient outcomes. Conversely, unnecessary hospital admissions can overburden ...

Early Identification of High-Risk Individuals for Mortality after Lung Transplantation: A Retrospective Cohort Study with Topological Transformers

Lung transplantation remains the only definitive treatment for patients with end-stage respiratory failure; however, it is burdened by a substantial r...

Falls in Assisted Living Facilities: Can AI improve documentation and reduce injury?

Falls among elderly residents in assisted living facilities (ALFs) are prevalent, costly, and frequently under-documented. AUGi, a wall-mounted device...

Hemi-brain growth as a biomarker for whole brain growth

Accurate cerebrospinal fluid (CSF) and brain volume estimation are important components for evaluating hydrocephalus treatments, including shunts and ...

Agentic Generative Artificial Intelligence System for Classification of Pathology-Confirmed Primary Progressive Aphasia Variants

Accurate clinical and pathological diagnoses are essential in neurodegenerative diseases, especially given the emergence of pathology-specific disease...

Clinical Implementation of an AI Algorithm for Substance Misuse Screening in Hospitalized Adults

Manual inpatient screening for substance misuse is labor-intensive and inconsistently applied. Evaluation of artificial intelligence (AI)–assisted scr...

Radiologic, Pathologic, and Deep Learning Predictors of Response to Immune Checkpoint Blockade in Renal Cell Carcinoma Patients Undergoing Post-Treatment Nephrectomy

Response assessment of primary kidney tumors in the consolidation cytoreductive and neoadjuvant settings offers a unique opportunity to inform postope...

Resting-state EEG and machine learning to investigate cortical connectivity as a biomarker in chronic mTBI

Mild traumatic brain injury (mTBI) is a heterogeneous condition with long-term sequelae, yet diagnosis in the chronic stage remains limited by relianc...

Machine Learning Analysis of Post-Acute COVID Symptoms Identifies Distinct Clusters, Severity Groups, and Trajectories

Questionnaires that capture patient-reported symptomatology provide low-cost but potentially high-value data for the de novo discovery of disease phen...

Investigating the Data Addition Dilemma in Longitudinal TBI MRI

Clinical machine learning (CML)for brain MRI often assumes that more data guarantees better performance, yet added samples can reduce accuracy when th...

Cerebral Cortical Reorganization After Intracerebral Hemorrhage in Children

Structural changes following pediatric intracerebral hemorrhage (ICH) caused by ruptured brain vascular malformations remain poorly understood. We con...

Predicting brain age for veterans with traumatic brain injuries and healthy controls: an exploratory analysis.

BACKGROUND: Traumatic brain injury (TBI) is associated with increased dementia risk. This may be driven by underlying biological changes resulting fro...

Jan 1 2025 40443792
Machine learning identifies genes linked to neurological disorders induced by equine encephalitis viruses, traumatic brain injuries, and organophosphorus nerve agents.

Venezuelan, eastern, and western equine encephalitis viruses (collectively referred to as equine encephalitis viruses---EEV) cause serious neurologica...

Jan 1 2025 40433315
Post-Transplant Liver Monitoring Utilizing Integrated Surface-Enhanced Raman and AI in Hepatic Ischemia-Reperfusion Injury Animal Model.

BACKGROUND: While liver transplantation saves lives from irreversible liver damage, it poses challenges such as graft dysfunction due to factors like ...

Jan 1 2025 40452789
Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study.

CONTEXT AND BACKGROUND: Depression has affected millions of people worldwide and has become one of the most common mental disorders. Early mental diso...

Jan 1 2025 40435349
AntBot-EX: Enhancing robot search efficiency in complex post-disaster environments.

In post-disaster scenarios, effective rescue operations hinge on deploying robots equipped with sophisticated path planning algorithms capable of navi...

Jan 1 2025 40402955
Leveraging artificial intelligence to promote COVID-19 appropriate behaviour in a healthcare institution from north India: A feasibility study.

Background & Objectives Non-pharmacological interventions (NPI) were crucial in curbing the initial COVID-19 pandemic waves, but compliance was diffic...

Jan 1 2025 40036109
PQD: Post-training Quantization for Efficient Diffusion Models

Diffusionmodels(DMs)havedemonstratedremarkableachievements in synthesizing images of high fidelity and diversity. However, the extensive computation...

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