AIMC Topic: Cross-Sectional Studies

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Inherited retinal disease pathway in the UK: a patient perspective and the potential of AI.

The British journal of ophthalmology
BACKGROUND: Inherited retinal diseases (IRDs) are the leading cause of blindness in young people in the UK. Despite significant improvements in genomics medicine, the diagnosis of these conditions remains challenging, and around 40% do not receive a ...

Retinal image-based deep learning for mild cognitive impairment detection in coronary artery disease population.

Heart (British Cardiac Society)
BACKGROUND: Coronary artery disease (CAD) is linked to an increased risk of mild cognitive impairment (MCI). Effective and convenient screening methods for identifying MCI from the CAD population are still lacking. This study aims to develop a deep l...

At-home wearables and machine learning capture motor impairment and progression in adult ataxias.

Brain : a journal of neurology
A significant barrier to developing disease-modifying therapies for spinocerebellar ataxias (SCAs) and multiple system atrophy of the cerebellar type (MSA-C) is the scarcity of tools to measure disease progression sensitively in clinical trials. Wear...

Utilizing artificial intelligence and medical experts to identify predictors for common diagnoses in dyspneic adults: A cross-sectional study of consecutive emergency department patients from Southern Sweden.

International journal of medical informatics
OBJECTIVE: Half of all adult emergency department (ED) visits with a complaint of dyspnea involve acute heart failure (AHF), exacerbation of chronic obstructive pulmonary disease (eCOPD), or pneumonia, which are often misdiagnosed. We aimed to create...

Can Artificial Intelligence Language Models Effectively Address Dental Trauma Questions?

Dental traumatology : official publication of International Association for Dental Traumatology
BACKGROUND/AIM: Artificial intelligence (AI) chatbots, also known as large language models (LLMs), have become increasingly common educational tools in healthcare. Although the use of LLMs for emergency dental trauma is gaining popularity, it is cruc...

Enhancing pathological myopia diagnosis: a bimodal artificial intelligence approach integrating fundus and optical coherence tomography imaging for precise atrophy, traction and neovascularisation grading.

The British journal of ophthalmology
BACKGROUND: Pathological myopia (PM) has emerged as a leading cause of global visual impairment, early detection and precise grading of PM are crucial for timely intervention. The atrophy, traction and neovascularisation (ATN) system is applied to de...

Machine learning-based predictive modeling of depressive symptoms in Chinese adolescents.

Journal of affective disorders
BACKGROUND: The aim is to develop prediction models by lifestyles indicators as well as socioeconomic status to predict the risk of depressive symptoms in adolescents, and to rank and explain these predictors.

When Machines Decide: Exploring How Trust in AI Shapes the Relationship Between Clinical Decision Support Systems and Nurses' Decision Regret: A Cross-Sectional Study.

Nursing in critical care
BACKGROUND: Artificial intelligence (AI)-based Clinical Decision Support Systems (AI-CDSS) are increasingly implemented in intensive care settings to support nurses in complex, time-sensitive decisions, aiming to improve accuracy, efficiency and pati...

The Evolving Role of Artificial Intelligence in Plastic Surgery Education: Insights From Program Directors and Residents.

Journal of surgical education
OBJECTIVE: To assess the current state of artificial intelligence (AI) policies, educational resources, and perceptions within U.S. plastic surgery residency programs from the perspectives of program directors (PDs) and residents.