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129 articles for “Diagnostic Accuracy”
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article
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AI-Driven Predictive Maintenance Framework for Intelligent Vehicle Health Monitoring
Abstract: The accelerated development of smart and connected car systems made the necessity to find the accurate and real-time predictive maintenance solutions which would minimize the number of unexpected failures as well as increase the cars on-road safety. The current paper proposes an artificial intelligence-based hybrid predictive maintenance system that combines Long Short-Memory (LSTM) networks and the XGBoost predictor to provide a potent vehicle fault diagnosis, Remaining Useful Life (RUL) prediction, …
Published in Trends in Machine design · Vol. 13, Issue 1, 2026 · pp. 1–17 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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ML-Enhanced Self-Healing Fiber-Reinforced Polymer Composites with Embedded IoT Sensors for Damage Prediction
Abstract: Fiber-reinforced polymer (FRP) composites are widely used in aerospace and structural systems; nevertheless, the potential for microcracking and fatigue-induced performance degradation remains an obstacle with respect to improved service life. Traditional self-healing methods, while performing well on a chemical level, often lack real-time diagnostic awareness and adaptive control. To circumvent this, we developed a machine-learning augmented self-healing FRP composite, in which a DCPD–Grubbs catalytic matrix was combined with IoT sensor …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 188–208 Read article
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Virtual Method to Predict Dental Disease
Abstract: The integration of technology and medicine in the healthcare domain has led to the emergence of inventive strategies to improve patient care and diagnostics. One such groundbreaking methodology is the utilization of Convolutional Neural Networks (CNNs) within the domain of deep learning, particularly for image recognition and processing tasks. In this paper, we propose a novel approach to image recognition that employs state-of-the-art deep learning algorithms to create a user-friendly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 8–15 Read article
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Smart Patient Monitoring and Motion Tracking System
Abstract: The integration of smart technologies in healthcare has revolutionized patient monitoring and diagnostics. This paper presents a Smart Patient Monitoring and Motion Tracking System designed for hospitals, leveraging EEG (Electroencephalogram) signals to track patient movements and monitor neurological health. The proposed system combines motion tracking with real time EEG signal analysis to enhance patient safety, especially for individuals prone to seizures, neurological disorders, or other mobility-related risks. The system employs …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 2, 2025 · pp. 9–23 Read article
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Cybersecurity of AI and IoT Integrated for Mechanical Industries
Abstract: By facilitating the concept of Industry 4.0, the intersection of artificial intelligence (AI) and the Internet of Things (IoT) has changed the mechanical industries. When combined, these technologies are advancing process optimization, predictive maintenance, real-time condition monitoring, and smarter automation. In order to give proactive system control and intelligent decision-making, AI algorithms mine large datasets generated via IoT devices for relevant patterns. In the meanwhile, IoT guarantees smooth communication between …
Published in Journal of Mechatronics and Automation · Vol. 12, Issue 2, 2025 · pp. 27–33 Read article
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Comparative Efficacy of Hybrid Capture 2 and Real-Time PCR in Detecting High-Risk HPV Genotypes for Cervical Cancer Screening
Abstract: Human papillomavirus (HPV) infection is a leading cause of cervical cancer, making early detection critical for effective prevention and treatment. Among the diagnostic methods available, Hybrid Capture 2 (HC2) and Real-Time Polymerase Chain Reaction (PCR) are widely used for detecting high-risk HPV genotypes, particularly HPV 16 and 18, which account for the majority of cervical cancer cases. This review aims to compare the efficacy of HC2 and Real-Time PCR in …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 2, Issue 2, 2024 · pp. 13–17 Read article
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An Evaluative Comparison of CD123 and CD66c as Biomarkers to Detect Minimal Residual Disease in B-Cell Acute Lymphoblastic Leukemia
Abstract: Background: B-cell Acute Lymphoblastic Leukemia (B-ALL) often shows lineage heterogeneity with lymphoid cells expressing myeloid markers. Minimal Residual Disease (MRD) refers to the small number of cancer cells that may remain in a patient's body after treatment and that are undetectable by standard diagnostic methods. In diseases like B-cell Acute Lymphoblastic Leukemia (B-ALL), MRD is a critical prognostic indicator, as its presence can signal a higher risk of relapse. In …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 7–12 Read article