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194 articles for “Healthcare Data Modeling”
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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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Centre Stage of Wireless Sensors in Healthcare: Application and Remote Patient Management
Abstract: The efficiency of wireless sensors in healthcare is greatly influenced by technological progress. The capabilities of these devices have been improved by advancements in wireless communication, data analytics, and sensor technologies. Patients may wear more comfortable, smaller, and more precise modern sensors. They have the ability to track many different physiological characteristics, ranging from simple vital signs to more intricate biomarkers. Understanding the massive volumes of data produced by wireless …
Published in Journal of Microcontroller Engineering and Applications · Vol. 11, Issue 2, 2024 · pp. 10–16 Read article
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Cognitive AI-Based Quality Control and Operational Optimization of Polymer Composites for Healthcare Applications
Abstract: The use of polymer composite materials in healthcare is on the rise because of their adjustable mechanical characteristics, biocompatibility and structural flexibility. Yet, it is difficult to ensure stable quality of such composites due to process-related defects, heterogeneity of the material and the lack of real-time adaptive control. The proposed study suggests the use of cognitive AI-based framework of quality control and optimization of operation of polymer composite systems which …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 571–591 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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Heart Disease AI-based Prediction: A Comparative Analysis
Abstract: The present investigation looks at how well various machine learning algorithms predict cardiac disease. Since heart disease is one of the major causes of death worldwide, early detection and precise diagnosis are essential for managing and treating the condition. Our goal is to enhance diagnostic processes and improve patient outcomes by leveraging machine learning techniques. Six widely-used machine learning algorithms are evaluated in this research paper. These algorithms were selected …
Published in Trends in Mechanical Engineering & Technology · Vol. 14, Issue 2, 2024 · pp. 21–29 Read article
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Design of Modelling Tool for Electronic Clinical Pathway based on Workflow and Standardised Terminologies
Abstract: It is very important to transform paper-based clinical pathways (CPs) into computer-readable format in order to integrate CPs into hospital information system (HIS). Modelling approaches of CPs include workflow management techniques, ontology and Petri net. Workflow-based modelling has a potential for representing sequenced medical activities in CPs, however previous approaches showed inadequate representation of medical content of CPs. Petri net and ontology-based modelling approaches have been widely used in modelling …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 12, Issue 3, 2024 · pp. 52–63 Read article
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Comparative of Encryption-Decryption Performance of (Binary, Gray- Scale, Color) Images Using Discrete Fractional Fourier Transform (DFRFT)
Abstract: The Discrete Fractional Fourier transform (DFRFT) provides an effective model of image encryption by further developing the classic Fourier transform by adding fractional orders, which increase the degrees of freedom. Owing to the omnipresence of digital media in many industries like education, healthcare, and entertainment, the mobility of visual data has become a significant issue to keep confidential. Images form one of the main ways of exchanging information and, therefore, …
Published in Research & Reviews : Journal of Physics · Vol. 15, Issue 1, 2026 · pp. 54–65 Read article
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Performance Forecasting in Solo Sports: Leveraging Psychometrics, Economic Analysis, and Cultural Insights for Predictive Excellence
Abstract: The science of performance forecasting in solo sports has transcended traditional metrics, embracing a multidisciplinary approach. This paper explores the integration of psychometrics, economic analysis, and cultural insights to predict athletic success. By leveraging psychological profiling, economic factors, and cultural dynamics, this study aims to establish a comprehensive model for forecasting athlete performance with heightened accuracy. In the realm of solo sports, where individual prowess dictates success, traditional performance forecasting …
Published in Recent Trends in Sports · Vol. 1, Issue 1, 2024 · pp. 35–44 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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Recent Advances in Content-based Image Retrieval: Techniques and Applications
Abstract: Content-based image retrieval (CBIR) plays a vital role in computer vision, driven by the increasing need for fast and accurate image retrieval across fields like healthcare, e-commerce, and digital libraries. This study offers a detailed review of CBIR methodologies, charting their progression from traditional feature extraction techniques, such as Local Binary Patterns (LBP), to contemporary deep learning-driven methods. The transformative impact of convolution neural networks (CNNs) is highlighted, emphasizing their …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 67–71 Read article
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Role of Fluid Engineering in Biomedical and Healthcare Systems: A Comprehensive Review
Abstract: Fluid engineering — the study and application of fluid behavior, transport, and interaction — has become a cornerstone of modern biomedical and healthcare systems. This review synthesizes the multifaceted roles fluid engineering plays across diagnostics, therapeutics, biomedical devices, and physiological modeling. Micro-fluidics enables precise manipulation of microliter and nanoliter volumes, facilitating rapid point-of-care diagnostics, high-throughput screening, and the fabrication of uniform nano particles for targeted drug delivery. In cardiovascular medicine, …
Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 1, 2026 · pp. 1–5 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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Machine Learning Approaches in Breast Cancer Diagnosis: Current Trends and Future Perspectives
Abstract: Since cancer is still one of the world's top causes of death, precise and effective detection techniques must be developed. Machine learning (ML) approaches have shown promise in recent years for enhancing cancer prognosis and detection. This paper presents a comprehensive review of the application of ML in cancer detection, focusing on various modalities including medical imaging, genomic data, and clinical records. We highlight the challenges associated with traditional cancer …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 14–20 Read article
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Skin Cancer Detection System Based on Machine Learning for Recognition of Cancerous Images
Abstract: Skin cancer ranks among the most prevalent types of cancer globally and poses significant risks when left untreated. Skin cancer arises when abnormal cells proliferate uncontrollably in the skin. This uncontrolled growth can be triggered by genetic mutations, exposure to ultraviolet (UV) radiation from the sun or artificial sources like tanning beds, or various other factors. In this, the early detection of cancer plays a crucial role in treatment and …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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An Efficient Deep Learning Classifiers Algorithm for Examining Public Perception of Covid SOPs
Abstract: In December 2019, Wuhan, China, reported the first coronavirus case, confirming the current pandemic. Following that, it swept across the entire world. The leading cause of this disease is still unknown, though. Governments are emphasizing physical distance and wearing masks in public places. The people mostly ignore the safety SOPs, which results in a surge in infected people rates and a healthcare burden on the national economy. Through the identification …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 10, Issue 1, 2023 · pp. 49–70 Read article
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A Hybrid Mathematical Model for Epidemic Outbreak Forecasting Using Machine Learning and Cloud Computing
Abstract: The increasing frequency of infectious disease outbreaks has emphasized the necessity for intelligent epidemic surveillance systems capable of predicting disease spread at an early stage. Conventional outbreak detection approaches rely heavily on delayed statistical reporting and manual monitoring techniques, resulting in reduced responsiveness during critical periods. This paper presents a mathematical predictive framework for epidemic outbreak detection using machine learning and cloud computing technologies. The proposed framework integrates the Susceptible–Infected–Recovered …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 01–06 Read article
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Advancements in AI-Driven Sound Spectrogram Analysis: From Deep Learning to Quantum and Neuromorphic Processing
Abstract: The rapid advancement of artificial intelligence (AI) has significantly reshaped the field of audio signal processing, with sound spectrogram analysis emerging as a central research focus. Spectrograms provide a rich time–frequency representation of audio signals, making them particularly suitable for data-driven learning approaches. This paper presents an in-depth and original review of modern AI-based techniques applied to spectrogram analysis, highlighting their growing impact across critical application areas such as healthcare …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 13, Issue 1, 2026 · pp. 01–06 Read article
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Innovations in Targeted Drug Discovery for Personalized Medicine
Abstract: Personalized medicine is revolutionizing modern healthcare by custoizing treatment plans to match an individual’s genetic makeup, protein expression, and metabomlic characteristics. Also referred to as precision medicine, this approach seeks to improve therapeutic outcomes, reduce adverse effects, and make efficient use of healthcare resources. The incorporation of various omics technologies—including genomics, proteomics, transcriptomics, metabolomics, and epigenomics—has greatly advanced our ability to understand disease biology and molecular variations specific to each …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 19–41 Read article
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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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Digital Health Interventions in Cardiovascular Pharmacology: A Review
Abstract: Cardiovascular diseases (CVDs) represent a formidable global health challenge, demanding innovative strategies for timely detection, effective management, and continuous monitoring. This study delves into the transformative potential of digital health interventions (DHIs), such as telemedicine and remote monitoring, in reshaping cardiovascular care paradigms. DHIs offer unparalleled accessibility, convenience, and personalized attention, thereby promising to revolutionize traditional approaches to cardiovascular health management. One of the foremost advantages of DHIs lies in …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 14, Issue 2, 2024 · pp. 1–5 Read article