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96 articles for “Explainable Artificial Intelligence”
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Advances in Deep Learning for Medical Image Analysis in the Era of Precision Medicine
Abstract: Medical imaging is fundamental to modern healthcare but analyzing the high-dimensional data requires advanced techniques. Manual image interpretation is time-consuming, subjective and limited in detecting complex patterns and minute details. Recent breakthroughs in Deep Learning offer transformative advances for unlocking clinically relevant information from medical images. This paper provides a comprehensive 6000+ word review of the current state-of-the-art Deep Learning techniques for medical image analysis including detailed coverage of key …
Published in Research and Reviews : Journal of Computational Biology · Vol. 12, Issue 2, 2023 · pp. 10–23 Read article
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AI-Based Early Diagnosis & Prevention of Diabetes
Abstract: The worldwide burden of Diabetes Mellitus, especially Type 2 diabetes (T2D) has escalated to a critical level. Early detection of diabetes is essential to reduce long‑term complications and healthcare costs. This study explores the use of artificial intelligence (AI) techniques to improve the early diagnosis and prevention of diabetes. We developed an AI model using the Random Forest algorithm, the model predicts diabetes risk based on clinical and lifestyle variables …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 13, Issue 2, 2026 Read article
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Study of Social Trends Prediction Using AI
Abstract: AI (Artificial Intelligence) has fundamentally changed the ability to analyze social trends by using large datasets to develop predictions about human behavior, public sentiment, and global events. Using methodologies such as Natural Language Processing (NLP), Time-Series Forecasting, and Graph-Based Social Network Analysis, AI is able to find hidden correlations in a variety of available datasets, from social media to economic indicators to public records, and fundamentally changes decision-making based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 19–29 Read article
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RoseRAG-Based Clinical Decision Support System for Precision Medication Safety
Abstract: Medication-related errors remain a major challenge in healthcare, contributing to adverse drug events, increased hospitalization rates, and substantial healthcare costs. Conventional Clinical Decision Support Systems (CDSS) primarily rely on rule-based mechanisms for identifying drug-related problems (DRPs), including drug–drug interactions, contraindications, dosing errors, therapeutic duplication, and medication omissions. Although effective in structured environments, these systems frequently generate excessive context-insensitive alerts, leading to alert fatigue and reduced clinical acceptance. Recent developments in …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Artificial Intelligence for Tracking Cognitive Deviation in Aging Populations: A Comprehensive Review of Techniques, Challenges, and Ethical Concerns
Abstract: Population aging is accelerating worldwide, and with it the burden of cognitive health conditions such as mild cognitive impairment (MCI), Alzheimer’s disease (AD), and dementia. Detecting and monitoring cognitive change early is central to timely intervention, yet conventional diagnostic tools often miss the subtle signals that appear before overt symptoms. Artificial intelligence (AI) has emerged as a promising complement to clinical assessment because it can work through high-dimensional data and …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 2, 2026 · pp. 27–37 Read article
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Study of Applications of Artificial Intelligence in Nuclear and Particle Physics
Abstract: Abstract This article explains the main concepts of the artificial intelligence, focusing on its history, its types and applications in Nuclear & Particle Physics. Deep learning method employs nonlinear functions to adjust the weight of the data wanted from the data background. By extracting meaningful data and fitting its shape with parameterized functions, deep learning method can capture main rules of the rude data, and make reliable predictions based on …
Published in Journal of Nuclear Engineering & Technology · Vol. 9, Issue 1, 2019 · pp. 29–33 Read article
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A Novel Analysis of Artificial Intelligence in Mechanical Engineering Application
Abstract: In this study, we have tried to explain the crucial role of Artificial Intelligence (AI) in the running of mechanical industry. The technology used these days in the machines is to aid the solution towards the real-world problems and complex situations. Many AI algorithms have been able to provide the solution to many engineering approaches. The importance of the artificial intelligence has automatized the mechanical engineering with smart machines and …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 5, Issue 3, 2018 · pp. 35–38 Read article
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Mechatronics Robot Navigation using Machine Learning through Prolog Programming Language
Abstract: A basic decision-making system is developed in this paper using Neural Network in Machine learningto explore a robot in concealed condition. The robot can move out of explicit labyrinths effectivelythrough modifying its bearing and speed persistently via the neural system model for machinelearning. Over the past several years, navigation tasks for mobile robots have been widely studied.There have been many attempts to introduce the usage of machine learning algorithms. Excellentperformance …
Published in Journal of Mechatronics and Automation · Vol. 8, Issue 1, 2021 · pp. 39–47 Read article
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A Review on Artificial Intelligence Techniques for Analyzing Deforestation and Illegal Logging Using Satellite Imagery
Abstract: Deforestation and illegal logging remain critical environmental threats, driving biodiversity loss, climate change, and socio-economic disruption. Conventional monitoring techniques frequently do not yield real-time, large-scale insights. Recent developments in Artificial Intelligence (AI), especially in deep learning and computer vision, have revolutionized the ability to analyze high-resolution satellite images for detecting deforestation and monitoring illegal logging. This review synthesizes recent developments in AI-driven approaches, highlighting convolutional neural networks (CNNs), anomaly detection …
Published in International Journal of Satellite Remote Sensing · Vol. 4, Issue 1, 2026 · pp. 1–9 Read article
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Artificial intelligence-integrated nanobiotechnology for precision medicine, smart diagnostics, and sustainable environmental applications
Abstract: Background: Nanobiotechnology integrates nanoscale materials with biological systems, enabling breakthroughs in drug delivery, biosensing, and environmental monitoring. However, the complexity of biological interactions and the vast parameter space of nano‑bio interfaces limit conventional design. Artificial intelligence (AI) offers powerful tools for modelling, predicting, and optimising these systems.Objective: This review provides a systematic, STM‑compliant overview of AI‑integrated nanobiotechnology across three domains: precision medicine (AI‑optimised nanocarriers, personalised therapeutics), smart diagnostics (AI‑powered nano‑biosensors, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Solution to Space Debris: IDRSS
Abstract: Debris has always been a matter of great concern in the field of space sciences. All the junk that can also be referred as the remains of the space projects that may include the rockets, satellites and much more is known as debris. This junk revolves in the space after getting detached from their host bodies and hence pose a hazardous threat for the possible space missions in the future …
Published in Journal of Materials & Metallurgical Engineering · Vol. 13, Issue 4, 2023 · pp. 24–33 Read article
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Advancing Asthma Management: The Synergy of Systems Biology, Artificial Intelligence, and Next-Generation Therapeutics
Abstract: Asthma is an inflammatory disorder of the respiratory tract that is chronic and heterogeneous in nature and has various effects on millions of people. Being a chronic inflammatory disease, asthma remains incurable and the major conventional treatments offer limited success due to the mask nature of its pathophysiology. Systems biology/(AI), and next-generation has greatly enhanced knowledge and the management of asthma. The approaches based on gene, transcript, protein, and metabolite …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 1–12 Read article
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Navigating the Dual Edge: A Comprehensive Technical Survey of Security, Privacy, and Countermeasures in the Era of Artificial Intelligence
Abstract: Artificial intelligence (AI) is seamlessly woven into vital sectors, such as self-driving cars, high-speed trading systems, and defense strategies; it has triggered a counterintuitive development in advanced cyberattacks. This survey paper attempts to perform an in-depth technical analysis of the “AI attack surface.” There are threats across three main vectors. Data integrity attacks focus specifically on examining “clean-label” poisoning and backdoor injection. Model confidentiality breaches discuss the mathematics behind model …
Published in Journal of Operating Systems Development & Trends · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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AI-Based House Price Prediction
Abstract: The housing market is one of the most dynamic and significant sectors of any economy, influencing both individual wealth and broader economic stability. Buyers, sellers, investors, and policymakers all rely on accurate housing price predictions. With the advent of artificial intelligence (AI) technologies, particularly machine learning algorithms, the task of house price prediction has seen remarkable advancements. This study provides a detailed overview of AI-based techniques for house price prediction. …
Published in Current Trends in Signal Processing · Vol. 13, Issue 3, 2023 · pp. 1–7 Read article
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Generative Artificial Intelligence with Emphasis on Large Language Models: Review and Current Trends
Abstract: Generative Artificial Intelligence deals with AI systems that generate new content, such as text, and images. It accomplishes this by using data patterns of texts and images that already exist. Generative AI began an era of major advancement in AI, producing more refined and human-like results. Large Language Models, LLMs, is a part of Generative AI with applications in Natural Language Processing such as text generation, translation, summarization, sentiment detection …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 40–46 Read article
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Toxicology 4.0: Integrating Artificial Intelligence, Big Data, Health Informatics, and Precision Analytics for Predictive Toxicity Assessment, Real-Time Toxicovigilance, and Personalized Patient Safety
Abstract: Background: Toxicology is undergoing a major transformation, increasingly described as Toxicology 4.0, driven by the integration of artificial intelligence (AI), big data analytics, health informatics, and precision analytics. Conventional toxicity testing is limited by high costs, lengthy timelines, and challenges in translating animal and low-throughput in vitro findings to humans. Aim and Objectives: To comprehensively evaluate the emerging role of Toxicology 4.0 in predictive toxicity assessment, real-time toxicovigilance, and personalized …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 2, 2026 Read article
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Adaptive E-Learning Algorithms and Heutagogy: A Systematic Analysis
Abstract: The proliferation of artificial intelligence (AI) and machine learning (ML) technologies has transformed the digital education landscape by enabling adaptive e-learning systems capable of personalizing content and optimizing learning paths. This study provides a systematic analysis of adaptive e-learning algorithms within the framework of heutagogy, an educational paradigm that emphasizes learner autonomy, self-direction, and capability development. The convergence of adaptive technologies with heutagogical principles offers new avenues for creating more …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 33–38 Read article
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Robotic Process Automation
Abstract: RPA is a software-based solution that automates rule-based human tasks or business processes that involve repetitive, routine tasks, structured data, and deterministic outcomes. According to recent studies, the use of RPA improves productivity, costs, speed, and error reduction. While robotic process automation (RPA) is a popular topic in the business world, academic research on the subject lacks a theoretical and synoptic analysis. This study provides a systematic yet concise description …
Published in Journal of Advancements in Robotics · Vol. 9, Issue 1, 2022 · pp. 29–36 Read article
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Open-Source Software Empowering Artificial Intelligence, Machine Learning, and Cyber Security: A Comprehensive Research Study
Abstract: Open-source software (OSS) has become a foundational pillar for rapid innovation across artificial intelligence (AI), machine learning (ML), and cybersecurity. This paper delivers a comprehensive, journal-length analysis of OSS-driven ecosystems, emphasizing collaborative development, transparency, and accelerated deployment. By providing freely available libraries, tools, and frameworks, OSS makes it easier for developers and researchers to experiment, build models, and deploy solutions quickly. This study examines how OSS can be combined with …
Published in Journal of Open Source Developments · Vol. 13, Issue 1, 2026 · pp. 08–15 Read article
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Reactive power compensation in modern power system using advanced control: A comprehensive survey
Abstract: Reactive power management is really important for keeping voltage steady, improving the quality of electricity, reducing energy loss during transmission, and ensuring modern power systems work well. As more renewable energy sources, power-electronic loads, distributed energy resources, and weak-grid conditions are added to the power system, it's becoming harder to use old methods for controlling reactive power. Flexible AC Transmission System (FACTS) devices, especially Static VAR Compensators (SVCs) and Static …
Published in Journal of Power Electronics and Power Systems · Vol. 16, Issue 3, 2026 Read article