Artificial Intelligence Medical Compendium

BACKGROUND & AIMS: Invasive measurement of hepatic venous pressure gradient (HVPG) is the gold standard for diagnosing clinically significant portal hypertension (CSPH, i.e. HVPG ≥10 mmHg), which indicates an increased risk of decompensation. We eval... read more 

Atmospheric particulate matter (PM) pollution is severe in southern Xinjiang, especially near the Taklimakan Desert, where air quality is affected by both dust and anthropogenic emissions. This study employs explainable machine learning in Hotan to i... read more 

This paper investigates target tracking systems with input time delays using output measurements and reinforcement learning to ensure tracking performance at a prescribed rate. We demonstrate that the delayed tracking problem can be addressed within ... read more 

Prior research on knowledge distillation has primarily focused on enhancing the process through logits and feature-based approaches. In this paper, we present a novel gradient-based perspective on the learning dynamics of knowledge distillation, reve... read more 

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OBJECTIVES: Six-region lung ultrasound (LUS) scores show good predictive value for predicting surfactant need in preterm infants but rely on a fixed threshold, which may lead to misclassification near the cut-off and lack data-driven justification fo... read more 

Artificial intelligence (AI) is rapidly transforming diagnostic imaging, raising important questions about its role as a collaborative tool or a potential replacement for human expertise. This rapid communication reviews current evidence on AI applic... read more 

PURPOSE: To explore perceived benefits, barriers and motivational factors related to exercising with the robotic device ROBERT® among patients undergoing rehabilitation following spinal cord injury (SC), and to explore physiotherapists' perspectives ... read more 

OBJECTIVES: Developing a deep-learning model for automated multi-tissue, multi-condition knee MRI analysis and assessing its clinical potential. MATERIAL AND METHODS: This retrospective dual-center study included 3121 MRI studies from 3018 adults, wh... read more 

PURPOSE: This study aims to develop real-time phase-contrast (PC) cardiovascular MRI with low latency. METHODS: In this study, a framework using golden-angle radial sequence and a deep-learning-based reconstruction network, named DLCNet, is proposed ... read more