AIMC Topic: Humans

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Enhancing medical students' diagnostic accuracy of infectious keratitis with AI-generated images.

BMC medical education
BACKGROUND: Developing students' ability to accurately diagnose various types of keratitis is challenging. This study aims to compare the effectiveness of teaching methods-real cases, artificial intelligence (AI)-generated images, and real medical im...

Deep learning for predicting myopia severity classification method.

Biomedical engineering online
BACKGROUND: Myopia is a major cause of vision impairment. To improve the efficiency of myopia screening, this paper proposes a deep learning model, X-ENet, which combines the advantages of depthwise separable convolution and dynamic convolution to cl...

Development of an explainable machine learning model for predicting device-related pressure injuries in clinical settings.

BMC medical informatics and decision making
BACKGROUND: Device-related pressure injury (DRPI) is a prevalent and severe problem for patients using medical devices. Timely identification of patients at high risk of DRPI is crucial for healthcare providers to make informed decisions and prevent ...

The association of life's essential 8 with prevalence of chronic respiratory diseases in adults: insights from NHANES 2007-2018.

BMC pulmonary medicine
OBJECTIVE: Chronic respiratory diseases (CRDs) and cardiovascular diseases (CVD) share common risk factors and frequently co-occur, leading to poorer outcomes. Life's Essential 8 (LE8), a novel metric for cardiovascular health, may provide insights i...

Construction and evaluation of a height prediction model for children with growth disorders treated with recombinant human growth hormone.

BMC endocrine disorders
BACKGROUND: Height gain in children with growth disorders undergoing recombinant human growth hormone (rhGH) therapy shows considerable variability. Predicting treatment outcomes is essential for optimizing individualized treatment strategies.

A machine learning model reveals invisible microscopic variation in acute ischaemic stroke (≤ 6 h) with non-contrast computed tomography.

BMC medical imaging
BACKGROUND: In most medical centers, particularly in primary hospitals, non-contrast computed tomography (NCCT) serves as the primary imaging modality for diagnosing acute ischemic stroke. However, due to the small density difference between the infa...

Longitudinal studies on breastfeeding among preterm infants: a scoping review.

BMC pregnancy and childbirth
AIM: This study aims to assess the exclusive breastfeeding rate among preterm infants, examine the factors influencing breastfeeding practices, and identify evidence-based interventions to enhance lactation support.

Applying deep learning techniques to identify tonsilloliths in panoramic radiography.

Scientific reports
Tonsilloliths can be seen on panoramic radiographs (PRs) as deposits located on the middle portion of the ramus of the mandible. Although tonsilloliths are clinically harmless, the high risk of misdiagnosis leads to unnecessary advanced examinations ...

Diabetic retinopathy detection using adaptive deep convolutional neural networks on fundus images.

Scientific reports
Diabetic retinopathy (DR) is an age-related macular degeneration eye disease problem that causes pathological changes in the retinal neural and vascular system. Recently, fundus imaging is a popular technology and widely used for clinical diagnosis, ...