Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 7,541 to 7,550 of 207,466 articles

STR-GNN: stability-regularized graph neural networks for suppressing spurious temporal variations in dynamic community detection.

Scientific reports
The study of temporal graphs frequently encounters spurious temporal fluctuations, wherein transient noise, inadequate observations, or ephemeral structural perturbations result in unstable and inconsistent community assignments. In dynamic networks,... read more 

Assessing Delay Patterns in Diagnosis and Care Among Breast Cancer Patients in Ethiopia.

Cancer reports (Hoboken, N.J.)
BACKGROUND: In Ethiopia, breast cancer patients often present with advanced-stage disease, leading to high mortality. This study aimed to quantify diagnostic and treatment intervals and identify their association with stage at presentation. AIM: The ... read more 

Deep learning for automatic segmentation of the inferior alveolar nerve using a hybrid CNN-transformer framework.

Scientific reports
Accurate identification of the inferior alveolar nerve (IAN) is essential for preventing nerve injury during dental and maxillofacial procedures such as tooth extraction, implant placement, and orthognathic surgery. However, manual annotation of the ... read more 

Predicting depressive symptoms among Chinese college students using recurrent neural networks with longitudinal data.

Scientific reports
College students face a higher risk of depression than their non-college peers. However, the predictors of depressive symptoms among college students and their relative importance remain inconclusive. This study aimed to develop predictive models for... read more 

CCDC6, a ferroptosis-related gene, modulates stemness features of pancreatic cancer cells in vitro.

BMC cancer
OBJECTIVE: Pancreatic cancer (PC) poses a significant threat to patient quality of life. Ferroptosis, a novel form of non-apoptotic cell death, is implicated in pancreatic tumorigenesis and therapy resistance. This study aims to identify key ferropto... read more 

A novel and accurate EEG emotion classification model based on multiple attention local binary patterns.

BMC medicine
BACKGROUND: Electroencephalography (EEG) signals play a crucial role in understanding brain activity because they provide useful information about real emotions and intentions. Many machine learning models have been used for automatic EEG-based emoti... read more