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649 articles for “Medical Data”
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Early Disease Detection Using Artificial Intelligence
Abstract: Growth in artificial intelligence and machine learning now make it possible for the healthcare sector to be totally transformed by a new chapter, particularly in the era of medical image analysis. This study focuses on harnessing these advancements to develop a sophisticated model for early disease detection across diverse medical domains, majorly in skin disease. By integrating diverse datasets and leveraging advanced algorithms, our methodology aims to identify subtle disease …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 11–19 Read article
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Development and Applications of a Simple Chalcone- Based Low Molecular Weight Ligand for Treating Nosocomial Infections due to Staphylococcus aureus and Escherichia coli
Abstract: Abstract Inspired from the available biological data of several imperative therapeutic scaffolds in several medicinal chemistry databases, thiophene-containing chalcone compounds were identified and the molecule was designed for treating various nosocomial infections. In one of the recent rational exploration, (E)-3-(4-methoxyphenyl)-1-(thiophen-2-yl)prop-2-en-1-one was synthesized in a single-step reaction, characterized comprehensively by using a few sophisticated spectroscopic instruments such as FT-IR spectroscopy, mass spectroscopy, and 1H-NMR spectroscopy, as well as CHN analyzer, and …
Published in Research and Reviews: A Journal of Medicine · Vol. 10, Issue 2, 2020 · pp. 14–18 Read article
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Smart Health Care System Study using IOT
Abstract: The proposed framework is a human services application in a joint effort with an IOT based medication box for individuals experiencing neurological imperfections, for example, Alzheimer's, Dementia, Parkinson's just as other age related issues. It is an activity made to focus on the most well-known indication that is absent mindedness. The medication box is a combination of detecting equipment framework and an android application that creates warnings dependent on different …
Published in Current Trends in Signal Processing · Vol. 11, Issue 2, 2021 · pp. 34–41 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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A Literature Review on Internet of Medical Things
Abstract: Artificial Intelligence (AI) is transforming healthcare by improving diagnostics, treatment planning, and patient management through data-driven insights and automation. The Internet of Medical Things (IoMT) represents a significant shift in modern healthcare, enabling real-time patient monitoring, data-driven decision-making, and enhanced medical outcomes. This literature review explores the architecture of IoMT, including perception layer, network layer, transport layer and application layer. It also thoroughly explores key challenges like ensuring data security, …
Published in International Journal of Wireless Security and Networks · Vol. 3, Issue 2, 2025 · pp. 23–34 Read article
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A summary continuation analysis evaluating the prevalence and predictors of diabetic retinopathy in newly diagnosed type 2 diabetic patients.
Abstract: Context: Diabetic retinopathy (DR), the leading cause of acquired blindness in adults, affects approximately 93 million people globally. It is a serious complication of type 2 diabetes, resulting from prolonged damage to the blood vessels in the retina. Although largely preventable and treatable, DR continues to be the main cause of vision loss among working-age adults and significantly impacts quality of life. While most studies on DR in Nepal have …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 2, 2024 · pp. 21–30 Read article
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Enhancing Glaucoma Diagnosis with Deep Learning: A Study Using ResNet-50 and DenseNet-121
Abstract: Glaucoma is a leading cause of irreversible blindness worldwide, mainly resulting from progressive optic nerve damage, often related to elevated intraocular pressure. Early detection is essential to prevent vision loss, but traditional diagnostic methods rely on specialized equipment and trained professionals, making large-scale screening difficult. This study uses a publicly available fundus imaging dataset to explore the effectiveness of deep learning models for glaucoma detection. These datasets provide medical images, …
Published in International Journal of Brain Sciences · Vol. 2, Issue 2, 2025 · pp. 9–18 Read article
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 Read article
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Optimized Hardware Realization of AES for High-Throughput FPGA Platforms
Abstract: The Advanced Encryption Standard (AES) is the predominant symmetric-key cryptographic algorithm used for securing digital communication across embedded systems, IoT devices, cloud infrastructures, and defense networks. Although software-based AES implementations offer flexibility, they often fail to meet the high-speed, low-latency, and energy-efficient requirements of modern real-time applications. Reconfigurable hardware platforms such as Field-Programmable Gate Arrays (FPGAs) provide a powerful alternative by enabling architectural customization, intrinsic parallelism, and optimized hardware acceleration. …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 3, Issue 2, 2025 · pp. 11–22 Read article
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Smart City for Sustainable Development- A Review
Abstract: Smart Cities will attempt to utilize innovation, data &information to further develop framework &administrations. Smart city includes flood of change wherever individuals of specific city get a wide range of fundamental administrations as drinkable water, disinfection, transportation, streets, streetlamps, office of training, data innovation, medical clinic, nursery, stopping &inns, rail routes, air terminal network, fire alleviation, including calamity the board , well strong waste administration plan, so that impeccable neatness …
Published in Trends in Transport Engineering and Applications · Vol. 9, Issue 1, 2022 Read article
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Text Analysis in Health Care Study Using IoT
Abstract: The Internet of Things (IoT) should be a recent buzzword that has steadily acquired acceptance (IoT). Organizations, governments, and the scientific community have already acknowledged the significance of the Internet of Things as a result of a surge in publications over the past few years. Despite scant research on goals and potential breakthroughs, IoT in health had a significant role in this development. In this study, the only method used …
Published in Journal of Computer Technology & Applications · Vol. 13, Issue 3, 2022 · pp. 11–18 Read article
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Transforming Cancer Care Through AI-Driven Machine Learning: Real-Time Patient Monitoring and Personalized Intervention Strategies
Abstract: Modern healthcare systems are being improved by artificial intelligence (AI) and machine learning (ML), particularly in the treatment of cancer. An AI-driven machine learning system for monitoring cancer patients in real time and offering tailored therapeutic methods is presented in this research. In order to track health issues in real time, the suggested system gathers ongoing health data from wearable sensors and integrates it with patient medical records. This data …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 15, Issue 2, 2026 · pp. 31–38 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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GSM Based ECG Monitoring System
Abstract: AbstractThe ultimate goal of this research paper is to develop an easy to use electrocardiogram apparatus with GSM module which will notify the concerned medical personnel after detecting heart beats and physical activity in real time. It is measured by one-lead ECG system which makes it easy to use even in absence of any medical assistance. This system is designed to capture and analyse ECG data of the patient in …
Published in Recent Trends in Electronics Communication Systems · Vol. 5, Issue 1, 2018 · pp. 12–16 Read article
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A Review of Recent Advancements in Machine Learning and Deep Learning Approaches for Pet Diseases Prediction
Abstract: This systematic study assesses recent developments in Machine Learning (ML) and Deep Learning (DL) approaches to predict pet diseases. With the increasing role of Artificial Intelligence (AI) in pet healthcare, this study identifies recent research trends, limitations, and future directions. A comprehensive search was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines in selecting 20 relevant studies from over 300 articles published between 2020 and …
Published in Research and Reviews : Journal of Veterinary Science and Technology · Vol. 14, Issue 3, 2025 · pp. 1–6 Read article
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Tuberculosis Treatment Outcomes among TB Patients at FenoteSelam District Hospital, West Gojjam Zone, Amhara, Northwest Ethiopia
Abstract: Introduction: Tuberculosis is a major public health problem throughout the world. One third of the world’s population is estimated to be infected with bacilli and hence at risk of developing active disease. It is the second leading cause of death from an infectious disease worldwide after HIV, which caused an estimated 1.8 million deaths. The main reason for this is the high rate of death as an unsuccessful outcome. Incomplete …
Published in Research and Reviews: A Journal of Medicine · Vol. 6, Issue 3, 2016 · pp. 1–8 Read article
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Artificial Intelligence in Healthcare for Implants and Tissue Regeneration: Advances, Challenges, and Future Directions
Abstract: Artificial intelligence (AI) has been a revolutionary influence in contemporary healthcare, especially in implant design, biomaterials research, and tissue regeneration. In regenerative medicine, AI facilitates predictive modeling, optimization, and decision-making via the analysis of intricate biological, material, and clinical information. This study analyzes current research on AI applications in implant technologies and tissue regeneration, specifically addressing scaffold engineering, biomaterial characterisation, stem cell and gene treatments, smart biomaterials, and implant planning. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
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The Social Media Misinformation Loop: An Analysis of Consumption and Sharing Behaviours among Medical Students
Abstract: Background: The contemporary information landscape is largely dominated by social media, which has emerged as a major source of information for medical students. This study aims to investigate the information consumption and sharing behaviours of medical students in Jammu and Kashmir, India, in the context of misinformation and its growing influence. Methods: A cross-sectional survey using a structured questionnaire was administered to 668 students from 13 medical colleges. The data …
Published in Research and Reviews: A Journal of Health Professions · Vol. 16, Issue 1, 2026 Read article
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Quantitative Image-Based Assessment of Degradation Patterns in Polymer-Based Medical Implants
Abstract: Polymer-based medical devices are widely used in clinical practice, where long-term material degradation can compromise performance and patient safety. Traditional polymer degradation studies predominantly rely on laboratory-based experiments, which often fail to capture real-world operational and usage conditions. In this study, a multimodal, data-driven framework is proposed for the quantitative assessment of degradation patterns in polymer-based medical devices using publicly available clinical failure data. Structured operational parameters, including cumulative usage …
Published in Journal of Polymer & Composites · Vol. 14, Issue 2, 2026 · pp. 1510–1518 Read article
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Assessing Efficacy and Safety: Oxytocin Monotherapy vs. Oxytocin + Carbetocin Combination Therapy
Abstract: Objective: Comparing the Effectiveness between Oxytocin monotherapy and Oxytocin + Carbetocin. Methods: A prospective, non-randomized, observational study focusing on 221 women with CS was conducted. The patients eligible based on inclusion and exclusion criteria were screened and final sample size was 139. Individual patient data including patient demographics, medical history, OT notes, pre and post CBC reports, and safety data were obtained from the patient records. The study compared between …
Published in International Journal of Tropical Medicines · Vol. 1, Issue 1, 2024 · pp. 40–51 Read article