Artificial Intelligence Medical Compendium

OBJECTIVES: Fractional flow reserve (FFR) and instantaneous wave-Free Ratio (iFR) pressure measurements during invasive coronary angiography (ICA) are the gold standard for assessing vessel-specific ischemia. Artificial intelligence has emerged to co... read more 

OBJECTIVES: Accurate preoperative classification of pulmonary nodules (PNs) is critical for guiding clinical decision-making and preventing overtreatment. This study aims to evaluate the predictive performance of artificial intelligence (AI)-based qu... read more 

Comorbid anxiety disorders are common among patients with major depressive disorder (MDD), but their impact on outcomes of digital and smartphone-delivered interventions is not well understood. This study is a secondary analysis of a randomized contr... read more 

The widespread use of pesticides and genetically modified (GM) crops has greatly improved agricultural productivity and food security. However, excessive pesticide application and the presence of exogenous proteins from GM crops pose significant risk... read more 

Recently, the Transformer-based tracking frameworks begin to prevail in visual tracking with huge success. However, both the two-stream and one-stream pipelines have some intrinsic flaws due to their structural characteristics. Under such case, a nov... read more 

Epilepsy is a neurological disorder characterized by transient and recurrent abnormal brain activity, often diagnosed through manual inspection extensive analysis of electroencephalogram (EEG) recordings. However, existing deep-learning seizure detec... read more 

Domain adaptive object detection (DAOD) aims to enable object detectors to perform well on an unlabeled target domain that differs from the source domain used for training. Among various approaches, mean-teacher self-training has emerged as a promisi... read more 

As a downstream product of transcriptional regulation, mRNA offers valuable insights into age-associated molecular changes and shows considerable potential for applications in age estimation. In this study, RNA sequencing was conducted on peripheral ... read more 

Time series forecasting is widely applied in fields such as energy and network security. Various prediction models based on Transformer and MLP architectures have been proposed. However, their performance may decline to varying degrees when applied t... read more 

Complex-valued neural networks (CVNNs) are particularly suitable for handling phase-sensitive signals, including electrocardiography (ECG), radar/sonar, and wireless in-phase/quadrature (I/Q) streams. Nevertheless, their interpretability and probabil... read more