Artificial Intelligence Medical Compendium

OBJECTIVES: There is an application for artificial intelligence (AI) to augment medical education. The aim of this study was to incorporate AI-powered cameras to quantify the learning curve and performance metrics associated with external ventricular... read more 

We present SurfDist, a convolutional neural network architecture for three-dimensional volumetric instance segmentation. SurfDist enables prediction of instances represented as closed surfaces composed of smooth parametric surface patches, specific... read more 

Smart buildings generate vast streams of sensor and control data, but facility managers often lack clear explanations for anomalous energy usage. We propose InsightBuild, a two-stage framework that integrates causality analysis with a fine-tuned la... read more 

Pain is an inherent part of human existence, manifesting as both physical and emotional experiences, and can be categorized as either acute or chronic. Over the years, extensive research has been conducted to understand the causes of pain and explo... read more 

Nonlinear computation is essential for a wide range of information processing tasks, yet implementing nonlinear functions using optical systems remains a challenge due to the weak and power-intensive nature of optical nonlinearities. Overcoming thi... read more 

Current challenges in developing foundational models for volumetric imaging data, such as magnetic resonance imaging (MRI), stem from the computational complexity of training state-of-the-art architectures in high dimensions and curating sufficient... read more 

Accurate regulation of calcium release is essential for cellular signaling, with the spatial distribution of ryanodine receptors (RyRs) playing a critical role. In this study, we present a nonlinear spatial network model that simulates RyR spatial ... read more 

Cold Atmospheric Pressure Plasma Jets (APPJs) show significant potential for biomedical applications, but their inherent complexity, characterized by nonlinear dynamics and strong sensitivity to operating conditions like tip-to-surface distance, pr... read more 

Batch normalization (BN) is a ubiquitous operation in deep neural networks used primarily to achieve stability and regularization during network training. BN involves feature map centering and scaling using sample means and variances, respectively.... read more 

The way a person moves is a direct reflection of their neurological and musculoskeletal health, yet it remains one of the most underutilized vital signs in clinical practice. Although clinicians visually observe movement impairments, they lack acce... read more