INTRODUCTION: Most patients suffering from neurological disorders endure varying degrees of upper limb dysfunction, limiting their everyday activities, with only a limited number regaining full arm use. Robotic and technological rehabilitation has be...
ChatGPT, a general artificial intelligence, has been recognized as a powerful tool in scientific writing and programming but its use as a medical tool is largely overlooked. The general accessibility, rapid response time and comprehensive training da...
INTRODUCTION: Delayed neurological sequelae is a common complication following carbon monoxide poisoning, which significantly affects the quality of life of patients with the condition. We aimed to develop a machine learning-based prediction model to...
Computer methods and programs in biomedicine
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BACKGROUND: The growing population of elderly neurocritically ill patients highlights the need for effective prognosis prediction tools. This study aims to develop and validate machine learning (ML) models for predicting 28-day mortality in intensive...
Neurological disorders are a major global health concern that have a substantial impact on death rates and quality of life. accurately identifying a number of diseases Due to inherent data uncertainties and Electroencephalogram (EEG) pattern overlap,...
IMPORTANCE: Decreasing mortality in the field of pediatric critical care medicine has shifted practicing clinicians' attention to preserving patients' neurodevelopmental potential as a main objective. Earlier identification of critically ill children...
The blood brain barrier (BBB) is an endothelial-derived structure which restricts the movement of certain molecules between the general somatic circulatory system to the central nervous system (CNS). While the BBB maintains homeostasis by regulating ...
In this NeuroView, we discuss challenges and best practices when dealing with disease-detection AI models that are trained on heterogeneous clinical data, focusing on the interrelated problems of model bias, causality, and rare diseases.
Classical approaches to diagnosis frequently rely on self-reported symptoms or clinician observations, which can make it difficult to examine mental health illnesses due to their subjective and complicated nature. In this work, we offer an innovative...
OBJECTIVES: Neurological emergencies pose significant challenges in medical care in resource-limited countries. Artificial intelligence (AI), particularly health chatbots, offers a promising solution. Rigorous validation is required to ensure safety ...