AIMC Topic: Female

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ConnectomeAE: Multimodal brain connectome-based dual-branch autoencoder and its application in the diagnosis of brain diseases.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Exploring the dependencies between multimodal brain networks and integrating node features to enhance brain disease diagnosis remains a significant challenge. Some work has examined only brain connectivity changes in patient...

Facial surgery preview based on the orthognathic treatment prediction.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Orthognathic surgery consultations are essential for helping patients understand how their facial appearance may change after surgery. However, current visualization methods are often inefficient and inaccurate due to limite...

Predictive Analysis of Amyotrophic Lateral Sclerosis Progression and Mortality in a Clinic Cohort From Singapore.

Muscle & nerve
INTRODUCTION: There is currently no comprehensive Amyotrophic Lateral Sclerosis (ALS) patient database in Singapore comparable to those available in Europe and the United States. We established the Singapore ALS registry (SingALS) to draw meaningful ...

Associations among white matter microstructural changes and the development of emotional reactivity and regulation in infancy.

Molecular psychiatry
Deficits in emotional reactivity and regulation assessed in infancy, including high levels of negative emotionality (NE), low positive emotionality (PE) and low soothability, can predict future affective and behavioral disorders. White matter (WM) tr...

Birth weight prediction using artificial intelligence-based placental assessment from macroscopic photo: a retrospective study.

Placenta
BACKGROUND: This study aimed to predict newborn birth weight through multifactorial analysis of macroscopic placental images using artificial intelligence (AI).

Feasibility of human ethomic biomarkers for the diagnosis and monitoring of hip osteoarthritis.

Journal of biomechanics
Radiographic imaging is typically used to diagnose osteoarthritis (OA). However, patients would typically be sent for imaging after they present to a physician because of joint pain. By this time, the condition is likely irreversible. This study aims...

GDM-BC: Non-invasive body composition dataset for intelligent prediction of Gestational Diabetes Mellitus.

Computers in biology and medicine
Gestational Diabetes Mellitus (GDM) refers to any degree of impaired glucose tolerance with onset or first recognition during pregnancy. As a high-prevalence disease, GDM damages the health of both pregnant women and fetuses in the short and long ter...

Validating Emotion Analysis on Social Media Text for Detecting Psychological Distress: A Cross-Sectional Survey.

Issues in mental health nursing
This study investigates the relationship between self-reported psychological distress and emotions in social media posts, using a deep learning-based emotion analysis model. A cross-sectional design was used, collecting data from Instagram and Thread...

Deep learning-based post hoc denoising for 3D volume-rendered cardiac CT in mitral valve prolapse.

The international journal of cardiovascular imaging
We hypothesized that deep learning-based post hoc denoising could improve the quality of cardiac CT for the 3D volume-rendered (VR) imaging of mitral valve (MV) prolapse. We aimed to evaluate the quality of denoised 3D VR images for visualizing MV pr...

Deep learning approach in undergraduate nursing students and their relationship with learning outcomes: A latent profile analysis.

Nurse education in practice
BACKGROUND: Deep learning approach plays a pivotal role in nursing education, equipping students with the critical thinking skills and knowledge necessary to address complex clinical challenges. However, nursing students exhibit diverse approaches to...