Artificial Intelligence Medical Compendium

This study explored nurses' perspectives on the adoption and utilization of artificial intelligence (AI) in clinical practice within a large university-affiliated health system in the southeastern United States. Through a survey enriched by open-ende... read more 

Septic shock remains one of the most severe complications of infection, defined by circulatory, cellular, and metabolic dysfunction and associated with persistently high mortality. The concept has evolved markedly, from early descriptions of "blood p... read more 

PURPOSE: Four-dimensional computed tomography (4D CT) imaging is essential for radiation therapy planning in thoracic tumors. However, current protocols tend to acquire more projection data than is strictly necessary for reconstructing the 4D CT, pot... read more 

ETHNOPHARMACOLOGICAL RELEVANCE: In Ayurveda, the potency of herbs is traditionally classified into three categories, namely, Sīta (cold), Uṣṇa (hot), and Unuṣṇa (neutral). In this study, a gold standard dataset of 627 herbs with their potency prefere... read more 

Achalasia is generally considered a progressive condition where esophageal deformity worsens over time; diagnostic delay results in the overdilated and tortuous esophagus.1 Major established tests for achalasia include high-resolution manometry (HRM)... read more 

Age-related macular degeneration (AMD) is a leading cause of irreversible vision loss in older adults. While anti-vascular endothelial growth factor (anti-VEGF) therapy and novel treatments for geographic atrophy have improved management, timely diag... read more 

Time series anomaly detection plays a crucial role in identifying significant deviations from expected behavior. Implicit Neural Representation (INR) has been explored for time series modeling due to its ability to learn continuous functions. The inh... read more 

The aging population is disproportionately affected by pain in the acute care setting. Due to the complexity of the pain experience, pain management presents with significant challenges. Recent advancements in advanced analytics and computational too... read more 

Support vector machines (SVMs) are widely utilized in health care research for tasks such as classification, regression, and outlier detection. These models function by developing hyperplanes that maximize the separation between different classes in ... read more 

Dataset pruning aims at selecting a subset of the data so that the model trained on the subset performs comparably to the one trained on the full dataset. In the era of big data, unsupervised pruning of the dataset can alleviate the issue of the expe... read more