AI, Volume 6, Issue 4

A central focus of this study was the methodology used to evaluate both humans and AI platforms, particularly in terms of their competitiveness and the implications of six key challenges to society resulting from the development and increasing use of...

Efficiently handling long contexts in transformer-based language models with low perplexity is an active area of research. Numerous recent approaches like Linformer, Longformer, Performer, and Structured state space models (SSMs), have not fully reso...

Background/Objectives: Artificial intelligence (AI) is increasingly influencing oncological research by enabling precision medicine in ovarian cancer through enhanced prediction of therapy response and patient stratification. This systematic review a...

Mind wandering is a common issue among schoolchildren and academic students, often undermining the quality of learning and teaching effectiveness. Current detection methods mainly rely on eye trackers and electrodermal activity (EDA) sensors, focusin...

Three-dimensional (3D) visual perception is pivotal for understanding surrounding environments in applications such as autonomous driving and mobile robotics. While LiDAR-based models dominate due to accurate depth sensing, their cost and sparse outp...

Background/Objectives: This article explores the use of Ancient Greek as a prompt language in DALL·E 3, an Artificial Intelligence software for image generation. The research investigates three dimensions of Artificial Intelligence’s abi...

(1) Acute pancreatitis (AP) is a medical emergency associated with high mortality rates. Early and accurate prognosis assessment during admission is crucial for optimizing patient management and outcomes. This study seeks to develop robust radiomics-...

Background/Objectives: This article addresses the challenge of stress detection across diverse contexts. Mental stress is a worldwide concern that substantially affects human health and productivity, rendering it a critical research challenge. Althou...

Detecting fake news has become a critical challenge in today’s information-dense society. Existing research on fake news detection predominantly emphasizes multi-modal approaches, focusing primarily on textual and visual features. However, desp...

The growing demand for telemedicine has highlighted the need for automated healthcare services, particularly in medical question classification. This study presents a deep learning model designed to address key challenges in telemedicine, including c...