Head Trauma

Efficacy of short-course bevacizumab for brain tumor radiation necrosis with a volumetric analysis.

PURPOSE: Radiation necrosis (RN) is a challenging complication of cranial irradiation, often requiring corticosteroids for management. This study evaluates the clinical and radiologic efficacy of a short-course bevacizumab (BEV) regimen for brain tumor RN, with a volumetric assessment. MATERIALS AND METHODS: We retrospectively analyzed 11 patients with MRI-confirmed RN who received two or three cy...

Use of Commercially Available Large Language Models to Generate Information Leaflets on Post-Intensive Care Syndrome: Clinical Utility Assessment.

BACKGROUND: Patients and their families without medical knowledge may find professional health care information difficult to understand. The use of large language models (LLMs) to simplify and translate complex medical content holds promise for improving comprehension while reducing the burden on health care providers tasked with delivering explanations. OBJECTIVE: This study aims to evaluate the ...

Integrated machine learning-bayesian receptor modelling framework for uncertainty-aware source apportionment in a non-stationary fluoride-contaminated coastal aquifer.

Fluoride contamination in coastal aquifers is difficult to evaluate because its mobilisation is controlled by overlapping and seasonally dynamic non-s...

Unified model for prediction of the strength of soils stabilized with xanthan gum using white-box machine learning.

Biopolymer-based soil stabilization has attracted increasing attention as a sustainable approach in geotechnical engineering. However, accurate predic...

Decoding seasonal irrigation suitability of drain water using integrated indexical, statistical, graphical and machine learning approaches.

SCOPE: Rapid urbanization and industrialization have exacerbated freshwater scarcity while simultaneously increasing wastewater generation, making the...

CT-based radiomic markers to predict late-onset seizures after traumatic brain injury.

Post-traumatic epilepsy (PTE) is a major long-term complication of traumatic brain injury (TBI), but early risk prediction remains imprecise. Radiomic...

Enhancing Anatomy Learning Through Enhanced 3D Visualization: A Study on Student Perception and Engagement in Museum-Based Education.

Effective anatomy education is essential for medical training. While traditional anatomy instruction provides essential foundational knowledge, its ef...

Artificial Intelligence in Breast Cancer Lymph Node Evaluation: Is Neoadjuvant Chemotherapy the Achilles' Heel?

CONTEXT.—: Artificial intelligence (AI) has demonstrated high accuracy in detecting lymph node (LN) metastases in treatment-naïve invasive breast canc...

Unveiling the Microvasculature: The Index of Microcirculatory Resistance and Its Expanding Role in Cardiovascular Care.

Index of microcirculatory resistance (IMR) is a cutting-edge, wire-based tool that advances the capability assessment of coronary microvascular functi...

Occupational and socioeconomic predictors of myocardial infarction and coronary heart disease: a machine learning analysis.

BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality worldwide. Although traditional cardiovascular risk models...

Intracranial compliance monitoring using pulse shape index in traumatic brain injury: relation to cerebral physiology and clinical outcome.

BACKGROUND: The intracranial pressure (ICP) pulse waveform reflects intracranial compliance. The pulse shape index (PSI), an artificial intelligence (...

[Use of artificial intelligence for next-gen anamnesis and communication in orthopedics & trauma surgery : From chatbots to ambient intelligence].

BACKGROUND: Against the backdrop of increasing patient volumes, rising case complexity, and physicians' limited time, AI-driven systems for anamnesis,...

Machine Learning-Based Prediction Model for Infectious Complications in Trauma and Its Association With In-Hospital Mortality.

BACKGROUND: Infectious complications, such as sepsis or catheter-related infections, are common and serious sequelae after trauma. Despite their clini...

Examining the utility of digital phenotyping for the prediction of intrusive experiences.

Background: Intrusive experiences related to witnessing a traumatic event are the core symptom of post-traumatic stress disorder (PTSD), and have been...

Enhancing fear of re-injury classification after ACL reconstruction by integrating biomechanical and electromyography data using multimodal machine learning methods.

Fear of re-injury after anterior cruciate ligament (ACL) rupture often hinders return-to-sport and has been linked to movement patterns associated wit...

Machine learning-based information flow analysis of ECG signals for long QT syndrome.

Cardiovascular diseases remain the leading cause of death worldwide, highlighting the need for non-invasive and cost-effective risk assessment tools. ...

Early identification of high-risk individuals for mortality after lung transplantation: A retrospective cohort study with topological feature engineering.

Lung transplantation remains the only definitive treatment for end-stage respiratory failure; however, it has substantial post-operative mortality ris...

Assessment of the Performance of Siemens Scopio Digital Morphology on Bone Marrow Aspirates in Onco-Hematology.

OBJECTIVES: Digital morphology (DM) systems assisted by artificial intelligence are increasingly being introduced into hematology laboratories; howeve...

AI-Driven Hemodynamic Detection of Self-Induced Daydreaming With EMG-Based Physiological Triggers During Pre- and Post-Prandial States Using fNIRS and EGG.

BACKGROUND: Daydreaming can be monitored either to avoid it while doing hands-on tasks or to enhance it to foster creativity. Although significant res...

Comparative Clinical Evaluation of "Memory-Efficient" Synthetic 3D Generative Adversarial Networks (GAN) Head-to-Head to State of Art: Results on Computed Tomography of the Chest.

Generative adversarial networks (GANs) are increasingly used to generate synthetic medical images, addressing the critical shortage of annotated data ...