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126 articles for “Diagnostic techniques”
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U-Net Based Approach for Automated Brain Tumor Classification
Abstract: Brain tumor detection and identification play vital roles in diagnostic procedures in the field of medicine, with the conventional analysis of MRI images requiring a lot of time and also subject to variability. The proposed study involves the use of a CNN-U-Net based approach for brain tumor detection and identification automatically. The study uses a database of 3,064 contrast-enhanced T1-weighted MRI images from 233 patients with the tumors of meningioma, …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 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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Tropical Medicine and Leishmaniasis: Unraveling the Complexities of a Neglected Tropical Disease
Abstract: Protozoan parasites of the genus Leishmania are the cause of the vector-borne disease leishmaniasis, which poses a serious threat to global public health in tropical and subtropical areas. Despite being common and having a significant effect on human health, leishmaniasis is still a neglected tropical disease, with little funding available for investigation and prevention. This article examines the relationship between leishmaniasis and tropical medicine, emphasizing the particular difficulties this intricate …
Published in International Journal of Tropical Medicines · Vol. 1, Issue 2, 2024 · pp. 29–39 Read article
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Nanotechnology-Enabled Biosensors for Early Disease Diagnosis and Personalized Healthcare Monitoring
Abstract: Nanotechnology has revolutionized the field of biosensors, enabling early disease diagnosis and personalized healthcare monitoring. Utilising the special qualities of nanomaterials—such as their high surface-to-volume ratio, remarkable electrical and optical capabilities, and customised surface chemistry—nanotechnology-enabled biosensors create extremely sensitive and focused diagnostic instruments. With previously unheard-of sensitivity and accuracy, these biosensors are able to identify and measure a wide range of biomarkers, such as proteins, nucleic acids, and tiny molecules. …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 26, Issue 1, 2024 · pp. 1–15 Read article
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Gold Nanoparticle Size, Biodistribution, and Toxicity: Insights from DualEnergy CT
Abstract: Dual-energy and spectral computed tomography (CT) have emerged as powerful platforms for noninvasive, quantitative mapping of nanoparticle biodistribution in vivo. By exploiting the energy-dependent attenuation profiles of high-atomic-number (high-Z) materials, these systems enable material decomposition and element-specific imaging, thereby distinguishing nanoparticle signals from those of soft tissues and conventional iodinated contrast agents. Photon-counting spectral CT further enhances this capability by binning individual photons into multiple energy channels, improving spatial resolution, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Employment of Solid-State Technology in Sensor Design: A Study
Abstract: The rapid evolution of sensor technologies has been driven by the demand for more precise, durable, and compact systems to meet the needs of modern industries, healthcare, and consumer electronics. Solid state technologies have emerged as a transformative force in sensor design, offering unprecedented performance, reliability, and integration potential. Unlike traditional sensors, which often rely on mechanical, electrochemical, or piezoelectric principles, solid state sensors leverage the intrinsic properties of materials …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 31–41 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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Preservation and Conservation Techniques of Manuscripts: A Bibliometrics Study
Abstract: India's manuscripts, spanning 5,000 years, are critical cultural, religious, and intellectual assets at risk from environmental factors and neglect. This study examines global trends in the preservation and conservation of manuscripts, focusing on traditional and modern techniques to protect these fragile documents for future generations. This descriptive study uses a bibliometric approach to analyze global research trends in manuscript preservation. By reviewing literature from databases such as Scopus and Google …
Published in Journal of Advancements in Library Sciences · Vol. 12, Issue 1, 2025 · pp. 39–50 Read article
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Cancer Chemotherapy-Induced Cachexia: Bridging Mechanisms, Management, and Future Therapies
Abstract: Involuntary weight loss, skeletal muscle atrophy, adipose tissue depletion, anorexia, and systemic inflammation are all symptoms of chemotherapy-induced cachexia, a complex illness. Although it is common, it remains poorly understood and is often referred to as an "orphan disease." This study covers the epidemiology, pathophysiology, clinical symptoms, diagnosis, treatment, and emerging treatment options for chemotherapy-induced cachexia. To comprehend the causes, clinical results, and therapeutic approaches, a literature-based synthesis of recent …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 17–26 Read article
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Fuzzy C-Means Clustering for Effective Segmentation and Classification of Brain Tumors in MRI Scans
Abstract: The paper discusses the importance of detecting and classifying brain tumors via MRI for effective treatment. It proposes a framework utilizing the Fuzzy C-means clustering algorithm for segmentation, demonstrating improved performance through real dataset validation. The model is trained on a large, annotated MRI dataset to identify and classify different tumor types, enabling machine learning-based classification into benign and malignant tumors. The MATLAB-based solution automates brain tumor feature extraction, aiding …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 23–28 Read article
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A Comprehensive Review on Nanostructured Polymer Composites for CT Imaging Contrast Enhancement in Brain Tumor Diagnosis
Abstract: The detection and characterization of brain tumors require high-resolution and non-invasive imaging modalities that have the ability of differentiating tumorous tissues and healthy brain tissues. Computed tomography (CT) can be included in this number because, in addition to providing speedy scans and penetration to deep tissue, the diagnostic capability in soft tissue organ such as the brain is poor despite low natural contrast. The review is dedicated to the emerging …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 148–162 Read article
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Progression in multi-omics and immunological research on host-parasite interactions: Transcriptomics, proteomics, genomics, metabolomics, and immune responses
Abstract: The interaction occuring between hosts and parasites is a quick and multi step-complex biological process that tries to influence disease outcomes. In recent years, multi-omics approaches, such as transcriptomics, proteomics, genomics, metabolomics, and immunological studies, have gathered substantial eye in dissecting these interactions at a microscopic level. These techniques enable a vast understanding of the molecular structures involved in parasitic infections and host defense mechanisms. This article reviews the advancements …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 1, 2025 Read article
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Analysis of White Matter, Gray Matter, and Cerebrospinal Fluid Alterations in Neurological Disorders: A Deep Learning Approach
Abstract: This paper investigates the role of white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) alterations in the pathophysiology of neurological disorders, including Alzheimer’s disease, Parkinson’s disease, schizophrenia, and epilepsy. By leveraging advanced deep learning methodologies, we aim to automate the segmentation and analysis of brain structures from MRI scans, enabling a more detailed and precise evaluation of their roles in disease progression. These techniques allow for the identification …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 3, 2024 · pp. 21–27 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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Unraveling Ulcerogenesis: A Comprehensive Delve of Enteric & Nonenteric Ulcers
Abstract: Enteric ulcers present a multifaceted landscape encompassing both peptic and non-peptic varieties, demanding a thorough exploration of their manifestations, causes, and pathophysiology. At the forefront of understanding lie pivotal factors such as Helicobacter pylori infection, nonsteroidal anti-inflammatory drugs usage, lifestyle choices, and stress, each wielding significant influence over ulcer development and progression. The intricate interplay of these factors underscores the complexity of enteric ulcer etiology. Helicobacter pylori infection—a prevalent culprit—inflicts …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 1, 2024 · pp. 25–40 Read article
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Nanofluids: Advanced Synthesis Methods, Innovative Applications, and Future Directions
Abstract: Nanofluids, a novel mixture of nanoparticles and base fluids, is an innovative blend that has appeared as a transformative advancement in heat transfer and thermal management technologies. This study is going to discuss advanced synthesis methods, properties, and extensive applications of nanofluids in various fields, such as biomedical engineering, electronics cooling, solar energy, and machining. Optimization techniques such as nanoparticle selection, concentration control, and computational fluid dynamics modelling are also …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 1–11 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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Chemiluminescence: Recent Developments and Photochemical Applications in Analytical Chemistry
Abstract: Chemiluminescence (CL) is the observable production of electromagnetic radiation from a chemical reaction, typically in the form of ultraviolet, visible, or infrared light. According to subjective yield, CL has either been directly emitted from electronically excited intermediate products, or it has been supported by another molecule to emit CL. Since the 1950s, CL has been supported as a valid analytical tool, with the descriptive issued scope being limited to content …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 2, Issue 1, 2024 · pp. 20–25 Read article
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Detection and Classification of Alzheimer’s Disease Using Deep Learning Technique
Abstract: It is crucial that people with Alzheimer's disease (AD) receive a proper diagnosis to begin preventative action before irreparable brain damage develops. Most people who suffer from Alzheimer's disease (AD), a neurological condition that progresses, are older than 65. The area of interest (ROI) in the hippocampus has been extensively studied for several purposes, including neurological illness research, stress development monitoring, and memory function analysis. Moreover, a connection between Alzheimer's …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 15–20 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