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151 articles for “diagnostic applications”
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Electromechanical Modeling of Microscale Fluidic Systems with Electro Kinetic
Abstract: Due to their capacity to carry out complex fluid manipulations at the microscale, microfluidic systems have become more popular in a variety of applications. For a variety of industries, including biomedical diagnostics, chemical analysis, and environmental monitoring, achieving precise and effective fluid control is essential. The electromechanical modeling of microscale fluidic systems using electro kinetic actuation is the main topic of this research study. We propose a thorough framework for …
Published in International Journal of Electro-Mechanics and Material Behaviour · Vol. 1, Issue 1, 2023 · pp. 18–22 Read article
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Artificial Intelligence for Improved Healthcare: A Case Study and Applications
Abstract: Artificial intelligence (AI) in healthcare ushers in a revolutionary period of innovation, but it also brings with it significant ethical dilemmas. This paper explores the complex relationship between AI and healthcare, emphasizing both its useful applications and the moral conundrums that arise. Ethical issues span a wide range, including patient privacy, transparency, accountability, and the unintentional reinforcement of biases in AI algorithms. Privacy concerns take center stage as healthcare providers …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 1–12 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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Advances in Polymer-Based Nanocomposites for Moisture-Sensitive Applications
Abstract: Polymer-based nanocomposites have emerged as promising materials in sensor technology due to their superior mechanical, electrical, and environmental stability. These advanced materials offer unique advantages, such as enhanced sensitivity, durability, and adaptability to various environmental conditions, making them highly suitable for sensor applications. One of the most significant breakthroughs in this field is the integration of semiconducting nanoparticles (NPs) within a polymer matrix, which has led to remarkable improvements in …
Published in Journal of Polymer & Composites · Vol. 13, Issue 4, 2025 · pp. 145–152 Read article
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Integrated Microfluidic Platform for Accelerated Catalytic Analysis: Enhancing Sensitivity and Efficiency
Abstract: In this study, we introduce a groundbreaking advancement in microfluidic technology tailored for catalytic and catalytic analysis. Our innovative microfluidic device integrates novel features aimed at augmenting sensitivity and accelerating analysis while ensuring reliability and user-friendliness. The hallmark of our device is the fusion of sample preparation and analysis functionalities within the microfluidic chip. By embedding sample preconcentration and purification modules, we achieve remarkable enhancements in sensitivity and detection limits. …
Published in Journal of Catalyst & Catalysis · Vol. 10, Issue 2, 2023 · pp. 51–27 Read article
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Clinical Medicine Done with Clinical Accuracy
Abstract: The advancement of clinical medicine has progressively underscored the significance of accuracy in diagnosis and therapy. This article examines the concept of "Clinical Medicine Administered with Clinical Precision," emphasising how innovations in diagnostics, data analytics, and personalised treatments are transforming the healthcare environment. Clinicians can provide therapy that is not only successful but also personalised to each patient's requirements by combining evidence-based practices with patient-specific factors including genetic profiles, comorbidities, …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 6–19 Read article
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AI-Enhanced Interpretation of Cardiac Troponins: Toward Predictive Precision in Myocardial Injury
Abstract: Background: Cardiac troponins (cTn) represent the gold standard biomarkers for myocardial injury detection, yet their interpretation remains challenging due to various confounding factors and clinical contexts. Artificial intelligence (AI) technologies provide remarkable possibilities to improve the interpretation of troponin levels by utilizing pattern recognition, predictive modeling, and clinical decision-making support. Objective: This review examines the current state and future potential of AI-enhanced cardiac troponin interpretation, focusing on machine learning applications, …
Published in Research and Reviews: A Journal of Medicine · Vol. 15, Issue 3, 2025 · pp. 1–9 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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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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Nuclear Diagnostic Imaging for PET Scan using Technetium-99m
Abstract: AbstractNuclear diagnostic procedures are used in almost every hospital worldwide on a daily basis. PET scan is the most commonly used nuclear medical imaging procedure. PET scan is considered a safer alternative to other nuclear diagnostic procedures. It is primarily used to identify the diseases, predict the possibility of occurrence of a particular disease, planning and analysis of a treatment. The PET scan has many applications but its only side …
Published in Journal of Nuclear Engineering & Technology · Vol. 8, Issue 2, 2018 · pp. 1–3 Read article
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Hyperspectral Image Compression and Classification: A Survey
Abstract: The applications of hyperspectral images (HSI) are many, which include agriculture, food quality, remote sensing, medical diagnostics and safety assessment. Hyperspectral image analysis has been used for detecting contaminants and identifying defects in food. It also utilizes advanced software and hardware tools hence allowing users to diagnose and detect pathologies. In this paper an avant-garde investigation about Hyperspectral image compression and classification techniques which can be used in various applications …
Published in Journal of Remote Sensing & GIS Read article
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Manufacturing Processes and 3D Printing of Health Diagnostic Tools: Economic Analysis of Open Source Frameworks
Abstract: Health diagnosis tools, for example, the incorporation of 3D printing into their manufacturing, drastically changed medical technology, providing cheap, customizable, fast tools in the field. This transformation has been accelerated by open-source frameworks that decrease dependence upon proprietary manufacturing and increase accessibility to diagnostic tools. Economic benefits of open-source 3D printing include reduced production costs, less dependence on global supply chains, and better equity of access to health care globally. …
Published in Journal of Open Source Developments · Vol. 12, Issue 1, 2025 · pp. 43–46 Read article
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Polymers In Low-Resource Biomedical Innovation: Maker Labs, DIY Devices and Ethics
Abstract: The low-cost biomedical devices have been prototyped and sometimes put into practice by maker laboratories and community "DIY" (Do-It-Yourself maker) innovators due to the fast-growing availability of polymer-based fabrication (desktop 3D printing, laser cutting, and simple molding). Nowadays, polymers such as PLA, PETG, TPU, and PEEK are used in a wide range of applications, including surgical guides and anatomical models, as well as assistive technology and diagnostic housings. Such innovations …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 108–119 Read article
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Leveraging AI and Machine Learning for Early Prediction and Prevention of Non- Communicable Diseases in Resource-Limited Settings
Abstract: Populations in these regions face persistent structural barriers, such as underdeveloped healthcare infrastructure, shortages of trained health professionals, and fragmented or incomplete health information systems. These limitations delay timely diagnosis, restrict access to preventive care, and compromise effective disease management. In recent years, rapid progress in artificial intelligence (AI) and machine learning (ML) has opened promising avenues to mitigate these challenges. Practical applications already emerging include mobile health platforms for …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 9–15 Read article
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AI-Driven Handwriting Identification and Verification Using Textural Features
Abstract: The last few decades have seen handwriting recognition and verification earn their mark in areas like forensics, healthcare, education, and digital security. This study delves into the role of artificial intelligence (AI), machine learning (ML), and deep learning techniques in handwriting analysis. It highlights the extraction of textural features as a precursor to identifying narrows between original handwriting and its forgery, whereby a few distinctive patterns such as stroke width, …
Published in International Journal of Electronics Automation · Vol. 3, Issue 1, 2025 · pp. 35–44 Read article
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A Neuromorphic-Inspired, Low-Power VLSI Architecture for Edge AI in IoT Sensor Nodes
Abstract: As the proliferation of Internet of Things (IoT) devices continues to rise, there is an increasing demand for real-time, energy-efficient artificial intelligence (AI) processing directly at the network edge. Traditional edge AI accelerators, often based on deep learning models like convolutional neural networks (CNNs), struggle to meet the ultra-low-power requirements of battery-constrained IoT sensor nodes. In response to this challenge, this study introduces a neuromorphic-inspired, low-power very- large-scale integration (VLSI) …
Published in Journal of Microelectronics and Solid State Devices · Vol. 12, Issue 2, 2025 · pp. 41–47 Read article
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A Study on Optical Stethoscope
Abstract: The traditional stethoscope, a staple in medical diagnosis, has remained relatively unchanged since its inception. However, with the advent of cutting-edge technologies, a revolutionary Optical Stethoscope design has emerged, poised to transform the field of medicine. In a breakthrough that promises to transform the medical landscape, a team of innovative engineers and researchers has unveiled the results of their pioneering work on optical stethoscope design. This revolutionary device is set …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 22–28 Read article
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Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 Read article
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Crispr Cas – Revolutionizing Modern Therapies and Beyond
Abstract: CRISPR-Cas technology has emerged as a transformative tool in modern molecular biology, revolutionizing both fundamental research and clinical applications. This RNA-guided gene-editing system enables precise and efficient genomic modifications, offering unprecedented potential for addressing genetic disorders, infectious diseases, and oncological conditions through innovative therapeutic interventions. The inherent specificity and programmability of CRISPR-Cas systems have facilitated breakthroughs in diverse fields, including precision medicine, regenerative therapies, and immuno-oncology. Beyond its therapeutic applications, …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 1, 2025 · pp. 25–38 Read article
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Detection of Brain Tumors from MRI Images Based On Development of Thinking Computer Systems Techniques
Abstract: Brain tumors are one of the common diseases of the nervous system and have great harm to human health, and even lead to death. The detection, segmentation, and extraction of contaminated tumour regions from Magnetic Resonance Imaging (MRI) pictures are major problems; yet, a repetitive and time-consuming task performed by radiologists or clinical experts relies on their experience. The many anatomical structures of the human organ can be imagined using …
Published in Current Trends in Signal Processing Read article