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311 articles for “detection limit”
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Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
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AI-Powered Pharmacovigilance: Revolutionizing Adverse Drug Reaction Detection, Reporting, and Future Perspectives-A Review
Abstract: Pharmacovigilance is very important in drug safety as it monitors, identifies and prevents adverse drug reactions (ADR). Conventional pharmacovigilance systems are usually limited by underreporting and delay in signal detection as well as the inability to scale up. The pharmacovigilance sphere is undergoing a seismic shift with the arrival of AI. The use of AI-driven tools, such as machine learning and natural language processing, is transforming how ADR detection is …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 3, 2025 · pp. 01–07 Read article
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Advances in Non-Invasive NIR-Techniques for Gout Detection and Measurement
Abstract: Recent advancements in non-invasive near-infrared (NIR) spectroscopy techniques have significantly improved the detection and measurement of gout, a common form of inflammatory arthritis. Traditional diagnostic methods for gout, such as joint aspiration and crystal analysis, are invasive and can be uncomfortable for patients. In contrast, NIR spectroscopy offers a promising alternative by enabling real-time, non-invasive assessment of uric acid levels and related biomarkers associated with gout. The integration of portable …
Published in International Journal of Toxins and Toxics · Vol. 2, Issue 1, 2025 · pp. 1–8 Read article
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Self-Driving Cars and Computer Vision: Enhancing Computer Vision for Autonomous Vehicle Navigation
Abstract: Autonomous vehicles, commonly known as self-driving cars, are transforming the transportation sector by aiming to enhance road safety, ease traffic congestion, and boost overall efficiency. Central to the operation of these vehicles is computer vision, which enables them to perceive and understand their environment. This paper examines how computer vision contributes to the navigation of autonomous vehicles and highlights its continuous developments. Specifically, it examines key challenges such as real-time …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 13, Issue 2, 2025 · pp. 1–10 Read article
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Jowar Millet Crop Monitoring and Analysis Robot (JMAR): A Smart Solution for Plant and Soil Health in Jowar Millet Farming
Abstract: Farmers cultivating jowar millet (Sorghum) face significant challenges in maintaining crop health and optimizing yield due to the limitations of traditional plant disease detection and soil health assessment methods. Visual inspection and indigenous knowledge are labour-intensive, time-consuming, and often inaccurate, while soil monitoring requires specialized equipment that is not always affordable or accessible. These issues hinder timely intervention and can lead to crop losses and soil degradation. To address these …
Published in Research and Reviews : Journal of Crop science and Technology · Vol. 14, Issue 2, 2025 · pp. 8–18 Read article
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Canine Ehrlichiosis and Its Diagnostic Techniques: Review
Abstract: Canine monocytic ehrlichiosis, caused by Ehrlichia canis is one of the important immuno-suppressive infectious vector-borne diseases of dogs. Importantly, canine ehrlichiosis can be caused by different Ehrlichia species, which are intracellular rickettsial organisms belonging to the order Rickettsiales and included in the family Rickettsiaceae. Ehrlichias are the obligate intracellular organisms that affects the host immunologic response. It is typically a disease of leukocyte and platelet manifested by an acute reduction …
Published in Research and Reviews : A Journal of Immunology · Vol. 10, Issue 1, 2020 · pp. 1–11 Read article
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DETECTION OF LUNG CANCER USING SOFT COMPUTING TECHNIQUES
Abstract: Cancer is a generic term that can affect any part of the body. Most cancers, 90%-95%, are because by environmental and lifestyle variables which cause genetic mutations. Inherited genetics account for 5% to 10% of the total. Early identification of lung cancer has improved patient survival and has been a vital study topic. It starts within the cells covering the bronchi and lung parts like bronchioles or alveoli. Due to …
Published in Research and Reviews : A Journal of Immunology · Vol. 13, Issue 2, 2023 · pp. 1–12 Read article
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Road Maintenance by Pothole Detection and Filling Robot
Abstract: Road infrastructure plays a vital role in ensuring safe and efficient transportation; however, potholes remain a major challenge due to their impact on road safety, vehicle maintenance costs, and traffic flow. Traditional pothole inspection and repair methods rely heavily on manual labor, making the process time-consuming, costly, and potentially hazardous for workers. To address these limitations, this paper presents a Pothole Detection and Filling Robot, an intelligent robotic system designed …
Published in Journal of Mechatronics and Automation · Vol. 13, Issue 2, 2026 · pp. 39–46 Read article
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A Review on the Impact of Artificial Intelligence on Cybersecurity
Abstract: When it comes to protecting against cyber threats, the use of AI is changing everything. Thanks to AI-powered technologies, organizations can now better foresee and handle potential intrusions. These solutions provide exceptional capabilities in identifying threats, monitoring in real time, and delivering predictive insights. But, with these innovations come significant hazards and difficulties, necessitating thoughtful deliberation and preventative measures. Artificial intelligence's impact on cybersecurity is explored in this article, looking …
Published in Journal of Artificial Intelligence Research & Advances Read article
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Efficient Malware Detection in Cybersecurity: Leveraging Advanced Data Structures for Enhanced Threat Identification
Abstract: The cybersecurity landscape is constantly changing with more advanced malware creating major challenges for detection systems. To address these challenges effectively, advanced data structures have become essential in optimizing how data is managed, processed, and analyzed for malware detection. This review paper delves into the role of several cutting-edge data structures—bloom filters, tries, hash tables, graphs, decision trees, and suffix trees—in enhancing the efficiency and accuracy of malware detection mechanisms. …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 32–40 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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Assessing the Increasing Incidence of Prostate Cancer in Urban Delhi: Risk Factors, Early Detection, and Treatment Challenges
Abstract: Background: Prostate cancer has emerged as the second most prevalent cancer among men in India, with rapidly increasing incidence rates in urban areas like Delhi. This rise is attributed to urbanization, lifestyle changes (high-fat diets, tobacco use, sedentary behavior), increased life expectancy, and improved diagnostics. Despite its growing burden, low awareness, limited screening programs, and treatment barriers hinder early detection and effective management. This study examines the epidemiological trends, risk …
Published in International Journal of Oncological Nursing and Practices · Vol. 3, Issue 2, 2025 · pp. 21–28 Read article
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Advances in Multiclass Oral Cancer Detection Using Spectroscopic and AI Techniques
Abstract: Oral cancer, primarily OSCC, is still a major health issue worldwide, especially in low-HDI countries. Early diagnosis is essential since survival rates for early detection are much higher than for late-stage detection. However, traditional methods like visual inspection and biopsy are time-consuming, invasive, and rely on the clinician's skill, which is a limitation in accessibility and efficiency. Oral cancer detection has just been revolutionized by recent advances in spectroscopic techniques, …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 39–48 Read article
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Automated Healthcare Support System with AI
Abstract: The Automated Healthcare Support System with Artificial Intelligence (AI) presents a smart and scalable digital solution aimed at improving the accessibility and efficiency of healthcare services. The system is designed to provide preliminary medical guidance, perform symptom-based analysis, and deliver health-related insights through an intuitive user interface. By enabling early identification of potential health conditions, it assists users in determining the necessity of professional medical consultation. The proposed platform utilizes …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 Read article
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Development and Validation of a Robust RP-HPLC Method for Rufinamide Quantification in Pharmaceutical Dosage Form
Abstract: The creation and validation of a simple, precise, and targeted reverse phase high-performance liquid chromatographic (RP-HPLC) approach allowed for the quantification of rufinamide in pharmaceutical dosage forms. With a mobile phase of methanol and water (50:50, v/v), the technique used a gradient mode Symmetry Qualisil gold C18 column (4.6 x 150mm, 5 μm). For the detection method, a flow rate of 1 mL/min was employed at 220 nm. During a …
Published in Emerging Trends in Personalized Medicines · Vol. 1, Issue 1, 2024 · pp. 25–32 Read article
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A Review of AI-Based Intrusion Detection Systems for Mobile Ad Hoc Networks (MANETs)
Abstract: Mobile Ad Hoc Networks (MANETs) comprise wireless networks that lack any conventional infrastructure . Their chief features include highly changing network topologies, lack of centralized administration, and open nature of communication, which collectively result in making MANETs of the wireless kind very susceptible to a diverse range of cyber-attacks like blackhole, greyhole, wormhole, flooding, Sybil and denial-of-service (DoS) among others. Conventionally, Intrusion Detection Systems (IDS) relying on static rule-based methods …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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Modelling and Electrical Characterization of Single Electron Transistor
Abstract: A nano-electronic device with low power consumption, high performance, and quantum effects is the single electron transistor (SET). It's used in charge sensor applications, infrared radiation detectors, and spectroscopy. However, it faces limitations in lithography, co-tunneling effect, low gain, high output impedance, and background charges. Therefore, prior simulation is needed to optimize SET's work function and understanding physics concepts. A master equation approach is used to propose a new model …
Published in Journal of Semiconductor Devices and Circuits · Vol. 10, Issue 3, 2024 · pp. 19–25 Read article
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Hadoop Based Cloud Data Security on Cloud Using Encryption Algorithm
Abstract: Cloud-computing is the typical creative pattern of computing technique for people to apply the Information-Technology its related works along with the cheaper capabilities of computing. The services offered on the web are extending from applying the cloud provider’s hardware and software to controlling the security and other issues. Securing the data from the malignant customers, a process of client-authentication have becomes a significant task. Several securities and the privacy problems …
Published in Journal of Computer Technology & Applications · Vol. 8, Issue 3, 2017 · pp. 40–48 Read article
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Improving The Accuracy of Medical Diagonosis Detection Using Machine Learning
Abstract: While accurate and timely medical diagnosis is a fundamental aspect of effective health care delivery, traditional methods have not been able to overcome major hurdles such as inefficiencies in data analysis with Gi Human Error as well as limitations in scalability. The “Improved Accuracy of Medical Diagnosis Detection Using Machine Learning” project seamlessly integrates advanced machine learning (M L) technologies with efficient preprocessing and feature selection techniques to outperform all …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 1–8 Read article
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Network Intrusion Detection System using Machine Learning and Deep Learning Approach
Abstract: Networks play a significant part in today’s world; fast internet and communication industries result in vast network size and data expansion. Furthermore, attackers aiming to launch various cyberattacks inside the system cannot be neglected. An IDS keeps track of the network’s software and hardware security to preserve its privacy, integrity, and accessibility. Despite the significant efforts of the researchers, current IDS continue to confront challenges in terms of accuracy rate, …
Published in Journal Of Network security · Vol. 10, Issue 1, 2022 · pp. 7–34 Read article