BACKGROUND: Under-5 mortality in Bangladesh remains a critical indicator of public health and socio-economic development. Traditional methods often struggle to capture the complex, non-linear relationships influencing under-5 mortality. This study le...
Alzheimer's disease (AD) is a common type of dementia, with mild cognitive impairment (MCI) being a key precursor. Early MCI diagnosis is crucial for slowing AD progression, but distinguishing MCI from normal controls (NC) is challenging due to subtl...
Lung cancer is a major cause of cancer-related deaths, and early diagnosis and treatment are crucial for improving patients' survival outcomes. In this paper, we propose to employ convolutional neural networks to model the non-linear relationship bet...
INTRODUCTION: Epilepsy is a prevalent chronic neurological disorder, with approximately one-third of patients experiencing intractable epilepsy, often necessitating surgical intervention. Deep brain stimulation (DBS) of the thalamus has been introduc...
BACKGROUND: Differentiating major depressive disorder (MDD) from bipolar disorder (BD) remains a significant clinical challenge, as both disorders exhibit overlapping symptoms but require distinct treatment approaches. Advances in voxel-based morphom...
The increasing demand for population-wide genomic screening and the limited availability of genetic counseling resources have created a pressing need for innovative service delivery models. Chatbots powered by large language models (LLMs) have shown ...
Dental traumatology : official publication of International Association for Dental Traumatology
Jun 9, 2025
AIM: The aim of this study was to evaluate the performance of ChatGPT-4o and Gemini Advanced artificial intelligence-based chatbots (AI-based chatbots) in providing emergency intervention recommendations for dental trauma with intraoral photographs o...
BACKGROUND AND OBJECTIVES: Brain aneurysm detection models, both in the literature and in industry, continue to lack generalizability during external validation, limiting clinical adoption. This challenge is largely due to extensive exclusion criteri...
BACKGROUND: Recently, the machine learning (ML) methods have been recommended to predict suicide attempts (SA). However, there is little literature reported the prediction models based on multiple machine learning methods of Chinese people and previo...
INTRODUCTION: Machine learning (ML), an artificial intelligence (AI) subfield, is increasingly used by Canadian workplaces. Concerningly, the impact of ML may be inequitable and contribute to social and health inequities in the working population. Th...
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