CONCLUSIONS: Further study of the responsiveness and specificity of plasma oxylipins to changes in zinc intake is warranted. →
A dangerous infection contracted in hospitals, ventilator-associated pneumonia is frequently caused by bacteria that are resistant to several drugs. It is one of the main reasons why patients in intensive care units become ill or die. This research aimed to determine the most effective empirical therapy of antibiotics for better ventilator-associated pneumonia control and to… →
Background and Objectives: Assessing pain deception is challenging due to its subjective nature. The main goal of this study was to evaluate the diagnostic value of pain deception using machine learning (ML) analysis with the Minnesota Multiphasic Personality Inventory-2 (MMPI-2) scales, considering accuracy, precision, recall, and f1-score as diagnostic parameters. Materials and Methods: This study… →
Your LinkedIn headline is often the first thing people notice when they visit your profile. It’s more than just a title—it’s a snapshot of your professional identity. For computer vision engineers, a strong headline can help you stand out in a competitive field, highlight your skills, and show how your expertise aligns with the latest… →
The pre-training of language models (LMs) plays a crucial role in enabling their ability to understand and generate text. However, a significant challenge lies in effectively leveraging the diversity of training corpora, which often include data from varied sources such as Wikipedia, blogs, and social media. Models typically treat all input data equivalently, disregarding contextual… →
Complex domains like social media, molecular biology, and recommendation systems have graph-structured data that consists of nodes, edges, and their respective features. These nodes and edges do not have a structured relationship, so addressing them using graph neural networks (GNNs) is essential. However, GNNs rely on labeled data, which is difficult and expensive to obtain.… →
Large language models (LLMs) have revolutionized natural language processing, enabling applications that range from automated writing to complex decision-making aids. However, ensuring these models produce factually accurate responses remains a significant challenge. At times, LLMs generate outputs that appear credible but are factually incorrect, a phenomenon often referred to as “hallucination.” This issue becomes particularly… →
Advancements in neural networks have brought significant changes across domains like natural language processing, computer vision, and scientific computing. Despite these successes, the computational cost of training such models remains a key challenge. Neural networks often employ higher-order tensor weights to capture complex relationships, but this introduces memory inefficiencies during training. Particularly in scientific computing,… →