AIMC Topic: Cross-Sectional Studies

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Cognitive decline assessment using semantic linguistic content and transformer deep learning architecture.

International journal of language & communication disorders
BACKGROUND: Dementia is a cognitive decline that leads to the progressive deterioration of an individual's ability to perform daily activities independently. As a result, a considerable amount of time and resources are spent on caretaking. Early dete...

Artificial intelligence for detecting keratoconus.

The Cochrane database of systematic reviews
BACKGROUND: Keratoconus remains difficult to diagnose, especially in the early stages. It is a progressive disorder of the cornea that starts at a young age. Diagnosis is based on clinical examination and corneal imaging; though in the early stages, ...

In-depth quantification of bimanual coordination using the Kinarm exoskeleton robot in children with unilateral cerebral palsy.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robots have been proposed as tools to measure bimanual coordination in children with unilateral cerebral palsy (uCP). However, previous research only examined one task and clinical interpretation remains challenging due to the large amoun...

Liver fibrosis classification from ultrasound using machine learning: a systematic literature review.

Abdominal radiology (New York)
PURPOSE: Liver biopsy was considered the gold standard for diagnosing liver fibrosis; however, with advancements in medical technology and increasing awareness of potential complications, the reliance on liver biopsy has diminished. Ultrasound is gai...

Medical students' patterns of using ChatGPT as a feedback tool and perceptions of ChatGPT in a Leadership and Communication course in Korea: a cross-sectional study.

Journal of educational evaluation for health professions
PURPOSE: This study aimed to analyze patterns of using ChatGPT before and after group activities and to explore medical students' perceptions of ChatGPT as a feedback tool in the classroom.

A cluster-based ensemble approach for congenital heart disease prediction.

Computer methods and programs in biomedicine
BACKGROUND: One of the most prevalent birth disorders is congenital heart diseases (CHD). Although CHD risk factors have been the subject of numerous studies, their propensity to cause CHD has not been tested. Particularly few research has attempted ...

A Cross Sectional Study of ChatGPT in Translation: Magnitude of Use, Attitudes, and Uncertainties.

Journal of psycholinguistic research
This preliminary cross-sectional study, focusing on Artificial Intelligence (AI), aimed to assess the impact of ChatGPT on translation within an Arab context. It primarily explored the attitudes of a sample of translation teachers and students throug...

A comprehensive segmentation of chest X-ray improves deep learning-based WHO radiologically confirmed pneumonia diagnosis in children.

European radiology
OBJECTIVES: To investigate a comprehensive segmentation of chest X-ray (CXR) in promoting deep learning-based World Health Organization's (WHO) radiologically confirmed pneumonia diagnosis in children.

Predicting long-term neurocognitive outcome after pediatric intensive care unit admission for bronchiolitis-preliminary exploration of the potential of machine learning.

European journal of pediatrics
PURPOSE: For successful prevention and intervention, it is important to unravel the complex constellation of factors that affect neurocognitive functioning after pediatric intensive care unit (PICU) admission. This study aims (1) to elucidate the pot...

Perspectives of Patients With Chronic Diseases on Future Acceptance of AI-Based Home Care Systems: Cross-Sectional Web-Based Survey Study.

JMIR human factors
BACKGROUND: Artificial intelligence (AI)-based home care systems and devices are being gradually integrated into health care delivery to benefit patients with chronic diseases. However, existing research mainly focuses on the technical and clinical a...