Artificial Intelligence Medical Compendium

Three-dimensional printing (3DP) holds significant potential for developing personalized pharmaceutical oral dosage forms (printlets). 3D printing has the advantage of fabricating complex geometric structures for versatile drug release profiles, enha... read more 

BACKGROUND: Artificial intelligence (AI) especially deep learning (DL) has significantly revolutionized medical image analysis, which include dental diagnostics. In endodontics, the combination of AI and CBCT provides automatic detection, classificat... read more 

The retrosplenial cortex (RSC) is a critical brain region that is activated during spatial memory tasks and plays a crucial role in the consolidation of long-term memory. Various classes of RSC excitatory neurons across different laminar layers serve... read more 

The neural foundations of the Dark Triad (DT) personality traits-narcissism, Machiavellianism, and psychopathy-remain largely unexplored despite their profound impact on social behavior. Previous research has indicated potential structural and functi... read more 

Identifying the potential miRNA-disease association (MDA) has a greater impetus to the development of drug prevention, treatment and other fields. For the traditional prediction methods, they are characterized by long time and large cost. With the co... read more 

BACKGROUND AND OBJECTIVE: Accurate preoperative prediction of the International Association for the Study of Lung Cancer (IASLC) grades is crucial for devising personalized treatment strategies for lung adenocarcinoma. The aim of this study was to de... read more 

Blood pressure (BP) measurement in both acute care and outpatient settings is essential, as conditions like hypertension and hypotension are common and often asymptomatic until organ damage occurs. These conditions significantly increase the risk of ... read more 

BACKGROUND: The study aimed to explore the risk factors of suicidal attempts (SA) in patients with major depressive disorders (MDD). METHODS: Cross-sectional analysis of 3247 MDD patients from the National Survey on Symptomatology of Depression (NSSD... read more 

Existing spectral Graph Neural Networks (GNNs) often rely on fixed polynomial bases or predefined propagation mechanisms, which limits their adaptability to real-world graphs with complex spectral properties and varying levels of homophily. To addres... read more 

Predicting the influence power of nodes in complex networks, particularly in large-scale scenarios, is a fundamental and challenging problem in network analysis. However, labeling nodes based on their influence power requires running computationally ... read more