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119 articles for “medical data processing”
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Physical Modeling of Mass Transport Processes in Extraterrestrial Landscapes
Abstract: Currently the progress in physical models based on mass transport in both the Earth's surface and extraterresterial landscape has been growing. It is a frame work involving different natural and made made processes including aeline process, fluid flow process, magmal movement, Geomagnetic stroms, and clould flow modesl etc. These process encorporates Physical models and appraches which help to simulate, compute and experiment in order to reduce complexity. However, their operating …
Published in International Journal of Universe · Vol. 1, Issue 2, 2025 · pp. 47–54 Read article
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Sensors based Human Visual System: e-Retina
Abstract: This study explores the potential of bio-inspired sensor design to replicate the adaptive and highly efficient nature of the human visual system and e-retina. This study presents a novel sensor array incorporating foveated vision principles and dynamic range adaptation mechanisms. Our study demonstrates the improved performance of this system in complex visual scenes, particularly in low illumination and high-contrast scenarios. This study highlights the advantages of mimicking biological principles in …
Published in Trends in Opto-electro & Optical Communication · Vol. 15, Issue 1, 2025 · pp. 14–22 Read article
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Artificial Intelligence Techniques for Smart Polymer Nanocomposite Materials and Industrial Applications
Abstract: Protecting sensitive material data, manufacturing processes, and intelligent monitoring platforms is essential for the fast development of innovative polymer nanocomposite systems in fields such as aerospace, medicine, electronics, automobiles, and energy. In order to safeguard, consistently enhance, and optimize distributed industrial systems that consist of polymer nanocomposite materials, this study presents an AI-driven cybersecurity and cloud computing architecture. The suggested solution employs artificial intelligence (AI), machine learning (ML), cloud computing, …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 Read article
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FutureGen – Predicting Genetic Health
Abstract: FutureGen is an intelligent web-based system developed to help couples assess the risk of genetic disorders in their future child through data-driven analysis. The system brings together modern web technologies and machine learning to offer accurate and accessible predictions. The frontend, built with React, provides an intuitive interface for user interaction, while a Flask-based backend API handles model inference and manages communication with the Supabase database, which securely stores user …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 Read article
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Evolving IoT: Based Smart Healthcare Monitoring System
Abstract: The continuous progress in technology has led to remarkable enhancements in various aspects of human life, including healthcare. Within the healthcare sector, practitioners and experts are embracing new technologies to significantly improve the implementation of medical services. The Internet of Things (IoT) has emerged as a crucial foundation for various innovative healthcare technologies, such as heartbeat sensors, ECGs, and blood pressure sensors, each equipped with microcontrollers to read and interpret …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 1, Issue 1, 2023 · pp. 17–27 Read article
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Modernizing Pharmacovigilance: Leveraging AI, Automation, and Real-World Data for Drug Safety
Abstract: Pharmacovigilance, or PV, is “the pharmacological science relating to the detection, assessment, understanding, and prevention of adverse effects, mainly long term and short-term adverse effects of medicines.” PV’s specific objectives are to increase patient care and safety when using medications and all medical and paramedical therapies; assist in evaluating the benefits, drawbacks, efficacy, and risks of medications, ensuring their safe, prudent, and more effective use; and promote clinical training, education, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 · pp. 12–21 Read article
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AI Activity to Enhance Productivity, Creativity, and Sustainable Development of AI in Healthcare
Abstract: The application of artificial intelligence (AI) in healthcare is revolutionizing the industry by fostering both productivity and creative approaches to patient care and medical research. This study explores how artificial intelligence (AI) is reshaping healthcare by streamlining workflows, improving diagnostic precision, and supporting personalized treatment plans. AI-powered technologies are reshaping the way medical professionals approach patient care, providing tools that not only automate routine administrative and clinical tasks but also …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 1, 2025 · pp. 21–29 Read article
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Design and Implementation of Low Latency 16-bit Full Adder
Abstract: In the new age world, modern technology has vast applications in various fields of engineering, medicine, and others. Digital electronics processing and systems play a vital role in the analysis and computation of data representation. Electronic systems have gradually become faster and smaller scale. The primary structural element of any modern ALU-based processor is an adder. Addition is a well-known extremely basic function that is employed in nearly all computing …
Published in Journal of VLSI Design Tools and Technology · Vol. 14, Issue 3, 2024 · pp. 21–31 Read article
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Machine Learning in Nuclear Medical Applications: A Review of Research Frontiers
Abstract: Nuclear medicine, encompassing PET, SPECT, and targeted radionuclide therapy, generates high-dimensional, quantitative data uniquely suited for machine learning (ML) analysis. This review synthesizes current research applications of ML across six key domains. Positron emission tomography (PET), single-photon emission computed tomography (SPECT), and targeted radionuclide therapy are examples of nuclear medicine modalities that generate high- dimensional, quantitative datasets that are particularly well-suited for machine learning (ML)-driven analysis. These imaging methods provide …
Published in Journal of Nuclear Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 19–24 Read article
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Improving Healthcare Outcomes with RF-enabled Health Information Systems
Abstract: Health Information Technology (HIT) plays a crucial role in improving healthcare by making medical data more accessible, accurate, and efficient. Using radio frequency (RF) technology, HIT enables the wireless sharing of important health information—like patient records, and treatments—between patients, doctors, and other healthcare providers. This helps reduce paperwork, cut costs, and improve the quality of care. By reducing the reliance on paper-based records, RF-based HIT helps streamline administrative processes, cut …
Published in International Journal of Radio Frequency Innovations · Vol. 3, Issue 1, 2025 · pp. 8–13 Read article
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Deep Learning Applications in Bone Fracture Detection for Improved Radiographic Diagnostics
Abstract: Bone fracture detection is a critical aspect of medical diagnostics, traditionally relying on manual interpretation of radiographic images by experienced radiologists. This discipline has undergone a revolution with the introduction of machine learning (ML), which can improve accuracy, shorten diagnosis times, and lessen human error. This study investigates the use of different machine learning methods to enhance and automate the identification of bone fractures in radiography pictures. We utilized a …
Published in International Journal of Optical Innovations & Research · Vol. 2, Issue 2, 2024 · pp. 17–22 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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AI Application in the Creation of Medications for COPD
Abstract: The crippling lung condition known as chronic obstructive pulmonary disease (COPD) is typified by a continuous restriction of airflow, which results in increased respiratory dysfunction and a reduced quality of life. The rising incidence of COPD worldwide emphasizes the pressing need for innovative pharmaceutical approaches to address the illness. Even though COPD care has advanced significantly, most current medications concentrate on symptom relief rather than disease change. This gap in …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 2, 2025 · pp. 01–05 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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Medical Science in the Digital Era: A Comprehensive Study on Computing in Healthcare
Abstract: Adding computers to medical science has changed how healthcare is delivered, how research is done, and how well patients do. This article talks about the many ways that computer technology is used in modern medicine, such as for diagnostic imaging, electronic health records (EHRs), telemedicine, surgical robotics, and research that is based on data. Improvements in artificial intelligence (AI) and machine learning have made it possible to make more accurate …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 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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Accelerate Drug Development with Pharmacokinetic Softwares
Abstract: During continuously evolving technologies and mechanized equipments, there has been a tremendous growth in the pharmaceutical sector over the past few decades. New technologies, software, devices, and techniques are being developed or researched upon with each passing day. By leveraging pharmacokinetic software, researchers can efficiently analyze vast datasets from preclinical and clinical studies, extracting actionable insights that inform decision-making early in the development cycle. This predictive capability not only accelerates …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Lung Cancer Detection and Classification Using Deep Learning
Abstract: Lung cancer is a disease that can be effectively treated if detected early. Various technologies, such as magnetic resonance imaging, isotopes, X-rays, and computed tomography scans, are employed for diagnosis. One of the most crucial strategies in combating cancer is early detection, which greatly enhances a patient’s likelihood of survival; this is where artificial intelligence plays a significant role. The approach proposed in this study leverages historical medical data to …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 3, 2024 · pp. 11–17 Read article
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Understanding of Research Bias in Herbal Medicine: A Comprehensive Review
Abstract: Background: The communication and generation of knowledge are central to research. In herbal medicine, with its deep historical roots, research must be methodologically rigorous and unbiased to validate traditional knowledge in modern contexts. Bias, defined as any tendency preventing objective evaluation of a research question, compromises validity and reliability. Objective: To highlight types of research bias in herbal medicine and discuss strategies for minimization to ensure credible and applicable findings. …
Published in Research & Reviews : Journal of Herbal Science · Vol. 15, Issue 1, 2026 · pp. 31–35 Read article