AIMC Topic: Young Adult

Clear Filters Showing 251 to 260 of 4802 articles

Visualizing functional network connectivity differences using an explainable machine-learning method.

Physiological measurement
. Functional network connectivity (FNC) estimated from resting-state functional magnetic resonance imaging showed great information about the neural mechanism in different brain disorders. But previous research has mainly focused on standard statisti...

Empowering Data Sharing in Neuroscience: A Deep Learning Deidentification Method for Pediatric Brain MRIs.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Privacy concerns, such as identifiable facial features within brain scans, have hindered the availability of pediatric neuroimaging data sets for research. Consequently, pediatric neuroscience research lags adult counterparts,...

Reirradiation for recurrent glioblastoma: the significance of the residual tumor volume.

Journal of neuro-oncology
PURPOSE: Recurrent glioblastoma has a poor prognosis, and its optimal management remains unclear. Reirradiation (re-RT) is a promising treatment option, but long-term outcomes and optimal patient selection criteria are not well established.

A deep learning algorithm for automated adrenal gland segmentation on non-contrast CT images.

BMC medical imaging
BACKGROUND: The adrenal glands are small retroperitoneal organs, few reference standards exist for adrenal CT measurements in clinical practice. This study aims to develop a deep learning (DL) model for automated adrenal gland segmentation on non-con...

Identification of relevant features using SEQENS to improve supervised machine learning models predicting AML treatment outcome.

BMC medical informatics and decision making
BACKGROUND AND OBJECTIVE: This study has two main objectives. First, to evaluate a feature selection methodology based on SEQENS, an algorithm for identifying relevant variables. Second, to validate machine learning models that predict the risk of co...

Is AI the future of evaluation in medical education?? AI vs. human evaluation in objective structured clinical examination.

BMC medical education
BACKGROUND: Objective Structured Clinical Examinations (OSCEs) are widely used in medical education to assess students' clinical and professional skills. Recent advancements in artificial intelligence (AI) offer opportunities to complement human eval...

Perspectives and Experiences With Large Language Models in Health Care: Survey Study.

Journal of medical Internet research
BACKGROUND: Large language models (LLMs) are transforming how data is used, including within the health care sector. However, frameworks including the Unified Theory of Acceptance and Use of Technology highlight the importance of understanding the fa...

TasteNet: A novel deep learning approach for EEG-based basic taste perception recognition using CEEMDAN domain entropy features.

Journal of neuroscience methods
BACKGROUND: Taste perception is the process by which the gustatory system detects and interprets chemical stimuli from food and beverages, involving activation of taste receptors on the tongue. Analyzing taste perception is essential for understandin...

Insulin resistance in type 1 diabetes is a key modulator of platelet hyperreactivity.

Diabetologia
AIMS/HYPOTHESIS: Individuals with type 1 diabetes are at increased cardiovascular risk, particularly in the presence of insulin resistance. A prothrombotic environment is believed to contribute to this risk but thrombotic pathways in type 1 diabetes ...

Mediating effect of AI attitudes and AI literacy on the relationship between career self-efficacy and job-seeking anxiety.

BMC psychology
As artificial intelligence (AI) technology quickly grows, college students have new worries and fears. Using Marx's theory of labour alienation, this study explores the complex relationship between college students' job-seeking anxiety (JSA) and care...