A5020374006- Cardiovascular Health and Disease Prevention
- Cerebrovascular and Carotid Artery Diseases
- Computer Graphics and Visualization Techniques
- Medical Image Segmentation Techniques
- Modular Robots and Swarm Intelligence
- Robotic Path Planning Algorithms
- Data Mining Algorithms and Applications
- Robot Manipulation and Learning
- Mathematical Biology Tumor Growth
North Carolina State University
2024
The University of Texas at Arlington
2024
Indian Institute of Technology Kanpur
2004
Large Language Models (LLMs) such as GPT and BERT demonstrate remarkable capabilities in various natural language processing (NLP) tasks. However, their performance is constrained by context length limitations, leading to inefficiencies extended text sequences. This paper explores the challenges posed limitations proposes innovative solutions combining Long Short-Term Memory (LSTM), Retrieval-Augmented Generation (RAG), Agentic Framework. We present an AI-powered solution tailored for...
Obstacle detection and collision avoidance capabilities are the cornerstone of service robotic manipulators, i.e., robots that can work safely in human environments. Though algorithms methods for already exist, they usually rely on complete CAD models environment. Such model difficult to obtain from dynamic environments involving persons moving unpredictable ways, thus reactive behaviors based real-time sensing seems be a more appropriate solution. This paper presents prototype skin robot...
One-dimensional (1D) cardiovascular models offer a non-invasive method to answer medical questions, including predictions of wave-reflection, shear stress, functional flow reserve, vascular resistance and compliance. This model type can predict patient-specific outcomes by solving 1D fluid dynamics equations in geometric networks extracted from images. However, the inherent uncertainty vivo imaging introduces variability network size vessel dimensions, affecting haemodynamic predictions....
Patient-specific computational modeling is a popular, non-invasive method to answer medical questions. Medical images are used extract geometric domains necessary create these models, providing predictive tool for clinicians. However, in vivo imaging subject uncertainty, impacting vessel dimensions essential the mathematical process. While there numerous programs available provide information about length, radii, and position, currently no exact way determine calibrate features. This raises...