AIMC Topic: Young Adult

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IdenBAT: Disentangled representation learning for identity-preserved brain age transformation.

Artificial intelligence in medicine
Brain age transformation aims to convert reference brain images into synthesized images that accurately reflect the age-specific features of a target age group. The primary objective of this task is to modify only the age-related attributes of the re...

Fully Hyperbolic Neural Networks: A Novel Approach to Studying Aging Trajectories.

IEEE journal of biomedical and health informatics
Characterizing age-related alterations in brain networks is crucial for understanding aging trajectories and identifying deviations indicative of neurodegenerative disorders, such as Alzheimer's disease. In this study, we developed a Fully Hyperbolic...

Neural Manifold Decoder for Acupuncture Stimulations With Representation Learning: An Acupuncture-Brain Interface.

IEEE journal of biomedical and health informatics
Acupuncture stimulations in somatosensory system can modulate spatiotemporal brain activity and improve cognitive functions of patients with neurological disorders. The correlation between these somatosensory stimulations and dynamical brain response...

Identifying the key factors of mercury exposure in residents of southwestern Iran using machine learning algorithms.

Environmental geochemistry and health
It is necessary to predict hair mercury (Hg) levels and specify the related effective factors to develop preventive strategies to reduce Hg exposure in different regions. This study is the first effort to investigate the effectiveness of eight machin...

Applying machine learning with MobileNetV2 model for rapid screening of vaginal discharge samples in vaginitis diagnosis.

Scientific reports
Vaginitis is a prevalent gynecological condition that impacts women's quality of life, with most women likely to experience it at least once. Traditional diagnosis involves manually observing vaginal discharge samples under a microscope. This process...

Artificial intelligence-assisted chatbot: impact on breastfeeding outcomes and maternal anxiety.

BMC pregnancy and childbirth
BACKGROUND: Artificial intelligence (AI) is increasingly used in healthcare interventions to provide accessible, continuous, and personalized patient support. This study investigates the impact of a mobile breastfeeding counseling application develop...

Artificial intelligence in focus: assessing awareness and perceptions among medical students in three private Syrian universities.

BMC medical education
BACKGROUND: Artificial intelligence (AI) has gained significant attention and progress in various scientific fields, especially medicine. Since its introduction in the 1950s, AI has advanced remarkably, supporting innovations like diagnostic tools an...

Application of machine learning algorithms to model predictors of informed contraceptive choice among reproductive age women in six high fertility rate sub Sahara Africa countries.

BMC public health
INTRODUCTION: Informed contraceptive choice is declared when a woman selects a methods of contraceptive after receiving comprehensive information on available alternatives, side effects, and management if adverse effect happens. Access to contracepti...

Predicting artificial neural network representations to learn recognition model for music identification from brain recordings.

Scientific reports
Recent studies have demonstrated that the representations of artificial neural networks (ANNs) can exhibit notable similarities to cortical representations when subjected to identical auditory sensory inputs. In these studies, the ability to predict ...

Medical students' knowledge, attitudes, and practices toward generative artificial intelligence in Egypt 2024: a Cross-Sectional study.

BMC medical education
BACKGROUND: Generative artificial intelligence (generative AI) has revolutionized the healthcare system for medical students and their educational process worldwide. Several studies assessed its efficacy in improving medical studies learning, and oth...