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Articles (9)

Editorial

Available Online: 02 Sep 2025

Revolutionizing Cardio-Oncology: Utilizing Artificial Intelligence to Build a Cutting-Edge Cancer Registry in Pakistan

Volume 2

Cardio-oncology is a specialized field dedicated to providing effective cancer treatment with minimal cardiotoxicity. This field also encompasses ways to ensure timely identification and appropriate treatment of cardiovascular disease caused by cancer treatment. Cancer patients experience the highest mortality from cardiovascular disease [1], thus signifying the importance of this field. Currently, the data on the outcomes of specialized cardio-oncology services is limited; there is a pressing need to start establishing..

Research Article

Available Online: 01 Sep 2025

Rewiring Education for a Super-Smart Society: Cognitive Integrity, AI Ethics, and the Future of Knowledge

Volume 2

Research Article

Published: 27 Jun 2025

The Impact of Toxic Effector Molecule TagX on the Amino Acid Conformation of the Hcp1 Monohexameric Ring in Acinetobacter baumannii Type VI Secretion System Utilizing Bioinformatics Tools and an AI System

Volume 2

Limited information is currently available regarding the contraction mechanism of the Hcp-1 hemolysin-coregulated protein within the type VI secretion system (T6SS) of Acinetobacter baumannii, particularly about the secretion of toxic effectors. This research aimed to evaluate the mechanism underlying the contraction of the Hcp1 nanotube in response to the putative toxic effector TagX protein by employing bioinformatics tools and the artificial intelligence (AI) DeepMind system. To achieve this goal, the..

Review Article

Published: 12 May 2025

Artificial Intelligence at the Crossroads of Engineering and Innovation

Volume 2

The field of Artificial Intelligence (AI) is progressively transforming various advanced engineering disciplines, including mechanical, civil, electrical, aerospace, environmental, and biomedical engineering, through improved design, manufacturing, maintenance, and optimization methodologies. Yet, the disjointed and specialized state of the art too frequently prevents the cross-disciplinary application of AI solutions due to disparate performance measures, which result in reduced knowledge transfer and exaggerated performance in segregated domains. This study overcomes these issues..

Perspective

Published: 28 Feb 2025

Precision Medicine for Autoimmunity: From CAAR-T Cells to AI-Driven CRISPR-Based Therapies, Challenges and Perspectives

Volume 2

This manuscript examines advancements in antigen-specific immunosuppression, as well as the potential and challenges of applying gene-editing technologies to autoimmune diseases driven by autoantibodies (AAbs). Current approved treatments fail to reach long-lived plasma cells (LLPCs), which may continue secreting pathogenic AAbs after immunobiological courses in some autoimmune illnesses. New approaches, some tested in vitro and some already undergoing clinical trials, such as the chimeric autoantibody receptor (CAAR)-T cells, BiTEs, affinity..

Systematic Review

Published: 07 Feb 2025

A Systematic Review on the Integrating Artificial Intelligence for Enhanced Fault Detection in Power Transmission Systems: A Smart Grid Approach

Volume 2

Modern electrical systems rely on sensors and relays for fault detection in three-phase transmission lines and distribution transformers, but these devices often face time complexity issues and false alarms. In this study, the fault detection accuracy is compared in models studied in 2023 and 2024 following PRISMA guidelines. The objectives were to identify fault types, utilize machine learning models to assess their predictive efficacy, and establish accuracy levels. To explore..

Research Article

Published: 29 Jul 2024

Mirror, Mirror on the Wall: Automating Dental Smile Analysis with AI in Smart Mirrors

Volume 1

This paper presents a smart diagnostic framework for dental smile analysis. To accurately and efficiently identify esthetic issues from a single image of a smile, a convolutional neural network (CNN) was trained. To overcome the limitations of scarce data, a diffusion model was employed to generate dental smile images in addition to manually curated data. The CNN was trained and evaluated on three datasets: all real images, all generated images,..

Review Article

Published: 31 Dec 2024

Distributed Reinforcement Learning for IoT Security in Heterogeneous and Distributed Networks

Volume 1

The explosive growth of the Internet of Things (IoT) has significantly increased networked devices within distributed and heterogeneous networks. Due to these networks’ inherent vulnerabilities and diversity, the proliferation of IoT devices presents substantial security challenges. Traditional security solutions face challenges in keeping up with the constantly changing threats in dynamic situations. This article reviews the application of distributed Reinforcement Learning approaches to enhance IoT security in dispersed and heterogeneous..