AIMC Topic: Young Adult

Clear Filters Showing 151 to 160 of 5268 articles

Integrative Deep Learning of Genomic and Clinical Data for Predicting Treatment Response in Newly Diagnosed Epilepsy.

Neurology
BACKGROUND AND OBJECTIVES: Epilepsy is a common neurologic disorder. Although antiseizure medications (ASMs) are the first-line treatment, identifying the most effective ASM for each individual remains a trial-and-error process. Genetic variation may...

Intra- and inter-field strength reproducibility of deep-learning based real-time cardiac MRI cine sequences with breath hold and in free breathing.

Scientific reports
To assess intra- and inter-field strength reproducibility of volumetric parameters using deep-learning-based real-time cardiac cine MRI during breath-hold (BH) and free-breathing (FB). In this prospective single-center study, 56 healthy adults underw...

Pitfalls in using ML to predict cognitive function performance.

Scientific reports
Machine learning analyses are widely used for predicting cognitive abilities, yet there are pitfalls that need to be considered during their implementation and interpretation of the results. Hence, the present study aimed at drawing attention to the ...

Inequity aversion toward AI counterparts.

Scientific reports
Human moral interactions often assume that resources should be allocated equitably, i.e., one should not take more than one's fair share. To what extent do people apply this assumption to social AI entities? Using a 21-round Ultimatum Game, we invest...

Generative AI-assisted clinical interviewing of mental health.

Scientific reports
The standard assessment of mental health typically involves clinical interviews conducted by highly trained clinicians. While effective, this approach faces substantial limitations, including high costs, high clinician workload, variability in expert...

Investigating the capability of deep learning models to predict age and biological sex from anterior segment ophthalmic imaging: a multi-centre retrospective study.

BMJ open
OBJECTIVE: To assess the capability of a convolutional neural network trained by transfer learning on anterior segment optical coherence tomography (AS-OCT) images, Placido-disk corneal topography images and external photographs to predict age and bi...

Individual innovativeness levels and levels of medical artificial intelligence readiness among nursing students: a cross-sectional and correlational study.

BMC medical education
AIM: This study, aimed to determine the individual innovativeness levels of nursing students and their readiness levels for medical artificial intelligence and the relationship between these two variables.

Identifying EEG-based neurobehavioral risk markers of gaming addiction using machine learning and iowa gambling task.

Biomedical physics & engineering express
Internet Gaming Disorder (IGD), Gaming Disorder (GD), and Internet Addiction represent behavioral patterns with significant psychological and neurological consequences. Affected individuals often disengage from routine activities and exhibit distress...

Academic misconduct and artificial intelligence use by medical students, interns and PhD students in Ukraine: a cross-sectional study.

BMC medical education
BACKGROUND: The issues regarding the use of artificial intelligence (AI) and academic integrity are important contemporary topics. There are no clear regulations governing the use of AI in academic institutions in Ukraine. This study aimed to explore...

Decoding covert visual attention of electroencephalography signals using continuous wavelet transform and deep learning approach.

Scientific reports
Covert visual attention decoding from EEG signals is a key challenge in cognitive neuroscience and brain-computer interface applications. Traditional approaches often rely on manual feature extraction and handcrafted pipelines, which limit scalabilit...