Artificial Intelligence Medical Compendium

OBJECTIVE: Recent advancements in deep learning have shown significant potential in ultrasound imaging. However, most approaches focus solely on image enhancement or segmentation, without integrating these tasks into a unified framework. To address t... read more 

The fungal bioluminescence pathway (FBP) offers a unique and sustainable system for continuous light emission through self-sustaining, nontoxic substrates. Recent advances in FBP-based substrate engineering, enzyme optimization, and metabolic refinem... read more 

BACKGROUND: Takotsubo cardiomyopathy (TTC) is an acute, reversible cardiac syndrome triggered by physical or emotional stress, involving complex multi-system interactions, with unclear mechanisms and variable prognosis across patient subgroups. OBJEC... read more 

BACKGROUND: The Hypotension Prediction Index (HPI) is a machine-learning algorithm designed to predict hypotension. by maintaining mean arterial pressure (MAP) above 65 mmHg. This meta-analysis evaluated whether HPI-guided management improves postope... read more 

The tumor microenvironment (TME) is a complex ecosystem of diverse cell types whose interactions govern tumor growth and clinical outcome. While multiple studies have extensively charted the TME's impact on immunotherapy, its role in chemotherapy res... read more 

Parkinson's disease (PD) is a progressive neurodegenerative disorder primarily characterized by the gradual loss of dopamine-producing neurons in the brain's substantia nigra. The hallmark motor symptoms of PD include tremors, bradykinesia (slowness ... read more 

OBJECTIVE: The aim of this study was to evaluate our first experience with the use of the artificial intelligence-based Endoleak Risk Index (ERI) in the planning of infrarenal endovascular aortic repair with special regard on its impact on clinical d... read more 

OBJECTIVE: Treatment of incompetent superficial veins can be associated with postoperative complications and pain, potentially impacting on patients' satisfaction. Early identification of patients at higher risk of complications could help tailor pos... read more 

BACKGROUND: Low health literacy affects nearly one-third of adults in the United States, and almost 68 million Americans speak a language other than English at home. These barriers to understanding medical information are associated with worse clinic... read more 

OBJECTIVE: Since categorization of dental crowding is a crucial parameter in orthodontic diagnosis and tooth-extraction decisions, we aimed to develop an automatic system to categorize crowding levels on intraoral photographs without space analysis. ... read more