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80 articles for “Real-Time Diagnostics”
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Artificial Intelligence based Point of Care Device in Advanced Medical Diagnostic Techniques
Abstract: Application of Point-of-Care Testing (POCT) at medical sites provides instant diagnostic results that help doctors make quick decisions for patient care. The traditional point-of-care testing equipment faces restrictions because they test single parameters and experience calibration problems in addition to inefficient data management systems. POCT technology benefits from the integration of Artificial Intelligence (AI) which creates a novel system to solve current operational limitations. The presented study introduces an intelligent …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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Data to Diagnosis: A Systematic Review of AI/ML in Healthcare
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are fast revolutionizing the diagnosis of healthcare by augmenting accuracy, speed, and efficiency. AI/ML technologies facilitate earlier and more accurate disease identification with advanced algorithms for image processing, predictive modelling, and pattern recognition, frequently outperforming conventional diagnostic techniques. This review delves into the key contribution of AI/ML in contemporary healthcare, such as its use in clinical data analysis, imaging reports, and patient histories …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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AutoGen Bike: A Self-Sustaining Smart Electric Bike with Integrated AI Safety Systems
Abstract: This is the paper which gives the information about the self-sustaining electric bike. This also tells the idea about how energy is produced during its usage. The “Auto gen bike” is the most useful aspect that can change the future of the electric bikes. This also helps in the conservation of natural resources and nature. This also helps in the accidents happening to the two-wheel vehicle. This is achieved by …
Published in Journal of Automobile Engineering and Applications · Vol. 12, Issue 2, 2025 · pp. 41–49 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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Sensors-Based Electric Machine Design for Industry
Abstract: The integration of advanced sensors is fundamentally changing the economics and reliability of electric machines. It moves design focus from minimizing material cost and adhering to conservative standards toward maximizing operational availability and energy efficiency. In the industry of tomorrow, the electric motor will not be a passive collection of coils and steel, but a self-diagnosing, self-optimizing, and perhaps even self-healing asset—a sentient motor—driven by its highly refined sixth sense, …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 1–10 Read article
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Automated Crop Disease Detection Using Convolutional Neural Networks
Abstract: Crop diseases contribute to major losses in agricultural production worldwide generating enormous economic costs. This study investigates the possibility of Convolutional Neural Networks (CNN) imaging techniques to auto-detect diseases associated with plants through image processing. A model was developed and trained on a publicly available plant disease dataset containing labeled images of several diseases. The CNN could classify various plant diseases with accuracy of 95%, precision of 92%, and recall …
Published in International Journal of Cheminformatics · Vol. 3, Issue 2, 2025 · pp. 7–15 Read article
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Phyto-Entrapped Carbon Dots as Emerging Nanomaterials for Anti-Cancer Activity
Abstract: Phytoconstituent-loaded carbon dots (C-dots) represent an innovative approach in targeted cancer therapy, combining the therapeutic power of plant-derived compounds with the advanced capabilities of nanotechnology. These ultra-small, biocompatible nanostructures offer excellent fluorescence, tunable surface chemistry, and low toxicity, making them ideal for drug delivery, bioimaging, and theranostic applications. Traditional phytochemicals often face challenges like poor solubility, low bioavailability, and high first-pass metabolism barriers that C-dots help overcome. C-dots synthesized through …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 3, 2025 · pp. 51–63 Read article
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Designing Aspects and Recent Advances in Digital Holographic Microscopy
Abstract: Recent advances in Digital Holographic Microscopy have been discussed in this paper, besides throwing some light on the designing aspects of optical components like beam splitter and neutral density filter for the optimization of system performance. Some important related subtopics like spectral resolution of digital holograms, and Fourier-synthesis holography have been technically discussed. The optimization of acoustical holographic components for use in renewable energy production is presented in this study. …
Published in Research & Reviews : Journal of Physics · Vol. 14, Issue 2, 2025 · pp. 06–18 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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Development of Adaptive Cruise Control (ACC) and Lane Keeping Assist (LKA) Systems for Electric Vehicles
Abstract: This project investigates an IoT-power Adaptive Driver Assistance System (ADAS) crafted to enhance the comfort, efficiency, and reliability of Electric Vehicles (EVs). By seamlessly integrating Adaptive Cruise Control (ACC) and Lane Keeping Assist (LKA), the system aims to metamorphose driving into a secure, more comfortable, and energy-conscious experience using low-priced sensors and microcontrollers. The ACC module relies on ultrasonic sensing element linked to a NodeMCU, which intelligently corrects vehicle speed …
Published in Journal of Instrumentation Technology & Innovations · Vol. 15, Issue 3, 2025 · pp. 1–6 Read article
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A Study of Optical Sensor in Clinical applications
Abstract: The escalating demand for precise, real-time, and minimally invasive diagnostic and monitoring tools in clinical practice has propelled the development of sophisticated sensor technologies. Among these, optical sensors have emerged as a cornerstone, leveraging the interaction of light with biological matter to translate molecular or cellular events into quantifiable signals. Their inherent advantages – including high sensitivity, specificity, rapid response times, non-ionizing nature, and potential for miniaturization – make them …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 1–7 Read article
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Fractal-Entropy Guided Adaptive Signal Reconstruction for Non-Stationary Biomedical and Communication Systems
Abstract: This paper presents a novel Fractal-Entropy Guided Adaptive Signal Reconstruction (FEG- ASR) framework designed for accurate processing of non-stationary signals in biomedical and communication systems. The proposed approach integrates fractal dimension analysis with entropy- based feature evaluation to capture the intrinsic complexity and irregularity of time-varying signals. By dynamically adapting reconstruction parameters based on fractal-entropy measures, the method effectively separates noise from meaningful signal components while preserving critical information. The …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 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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Antimicrobial Resistance and AI-Based Strategies for Rapid Pathogen Detection
Abstract: Antimicrobial resistance (AMR) has become a major global health threat, significantly reducing the effectiveness of antimicrobial therapies and increasing the burden of infectious diseases worldwide. The rapid emergence of multidrug-resistant pathogens has created an urgent need for faster, more accurate, and scalable diagnostic approaches to support timely treatment and effective infection control. Artificial intelligence (AI) has emerged as a promising technology capable of transforming pathogen detection and AMR surveillance through …
Published in Recent Trends in Infectious Diseases · Vol. 3, Issue 2, 2026 · pp. 26–36 Read article
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Advances in Nanotechnology-based Biosensors: Enhancing Sensitivity and Specificity in Biomedical Diagnostics
Abstract: This study provides an in-depth exploration of the rapidly evolving field of nanotechnology-based biosensors, emphasizing their significant impact on biomedical diagnostics. The integration of cutting-edge nanomaterials, including nanoparticles, nanowires, and quantum dots, has catapulted biosensing technology to new heights, yielding unprecedented gains in sensitivity and specificity, and revolutionizing the detection of biomolecules. The study highlights various types of nanobiosensors, including optical, electrochemical, and magnetic, each offering unique advantages for detecting …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 2, 2024 · pp. 26–32 Read article
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Magnetic and Radioactive Nanoparticles for Improved Theranostics and AI Assisted Radiation Therapy
Abstract: Nanoparticles based therapeutic and theranostics technique is becoming an active area of research in nanomedicine. The sensitivity, biocompatibility, and stability of magnetic and radioactive nanoparticles determine their functionality. This research highlights the impacts of magnetic and radioactive nanoparticles on therapeutic techniques namely, cell therapy, gene therapy, and tissue regeneration. Then, it is intended to brief a principal role of these therapeutic techniques to envisage theranostics medicine and radiation therapy using …
Published in International Journal of Advance in Molecular Engineering · Vol. 3, Issue 2, 2025 · pp. 10–21 Read article
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Modern Chemistry & Chemical Technology in Sensor Formation
Abstract: The field of sensor formation stands at the vibrant intersection of modern chemistry and chemical technology, driven by an insatiable demand for precise, rapid, and sensitive detection across myriad applications. This paper explores the foundational and transformative role these disciplines play in engineering next-generation sensing platforms. Modern chemistry, through its atomic-level precision in synthesizing novel responsive materials – ranging from advanced polymers and supramolecular architectures to cutting-edge nanomaterials like graphene, …
Published in Journal of Modern Chemistry & Chemical Technology · Vol. 17, Issue 1, 2026 · pp. 1–9 Read article
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Leveraging Artificial Intelligence (AI) and Digitalization of Community Health Screening in Unani Medicine: Bridging Tradition with Technology – A Perspective Review
Abstract: AI and digitalization bring a great opportunity for reforming and even improvement of traditional healthcare systems in Unani physiology. This review, therefore, observes the important role played by AI and digital health solutions in modernizing health screening and diagnostic procedures in Unani medicine, thereby bridging traditional healing practices with contemporary technological advancement. AI refers to the advantages that may accrue via wearable health devices and telemedicine in real-time monitoring, early …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 2, 2025 · pp. 20–31 Read article
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Leveraging Information Technologies (IoT, Sensor Technologies, AI, and Data Analytics) in Healthcare and Agriculture
Abstract: This paper explores the powerful convergence of digital technologies — the Internet of Things (IoT), Sensor Technologies, Artificial Intelligence (AI), and Data Analytics — in transforming healthcare and agriculture. Both sectors face pressing global challenges: rising population demands, environmental stress, disease burdens, unequal access to services, and food insecurity. Conventional systems alone cannot meet future needs. However, technology-driven, real-time data-driven systems offer innovative solutions: from automating diagnostics to forecasting pest …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 20–28 Read article
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Innovations in Healthcare IT for Enhanced Patient Outcomes
Abstract: Healthcare IT innovations are transforming medical services by enhancing diagnostics, improving patient management, and optimizing resource utilization. The integration of advanced technologies has led to significant improvements in healthcare delivery, enabling more accurate diagnoses, efficient treatments, and seamless data management. One of the most impactful advancements is Electronic Health Records (EHR), which facilitate centralized patient data storage, allowing healthcare providers to access and update records in real-time. Telemedicine has revolutionized …
Published in Current Trends in Information Technology · Vol. 15, Issue 2, 2025 · pp. 19–23 Read article