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357 articles for “Patient data”
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Personalized Therapy Using Drug Delivery Devices
Abstract: The persistent challenge in modern medicine lies in inter-patient heterogeneity, rendering standardized drug dosing protocols suboptimal for many chronic conditions. Traditional pharmacokinetics fail to account for real-time biological fluctuations, leading to cycles of ineffective treatment or dose-limiting toxicity. This paper explores the critical intersection of advanced drug delivery devices (DDDs) and personalized medicine, positioning these technologies as the vital link translating genomic and biological data into tangible, patient- specific interventions. …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 53–62 Read article
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Remote Monitoring Sensor Systems and Applications in Health Informatics: Fostering Shell Programming
Abstract: The fascination of sensor systems has been promising for health informatics as their direct initiative for real-time information by observing its accuracy that was required at the time for data collection, monitoring and analysis to improve patient well-being and health system administering. By integrating these systems with wearable devices, biomedical sensors, and other IoT-enabled technologies, patients can experience continuous health tracking, early disease detection, and remote patient monitoring. For example, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 Read article
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Experimental Study on Heart Disease Prediction Using Different Machine Learning Algorithms
Abstract: Heart disease which can also be referred to as the cardiovascular disease is one of the raising concerns in today’s world. It is one of the major health problems causing death among humans irrespective of the age group and therefore has made it necessary to look into different medical factors that are required to predict the same in advance using the collected historical datasets of various patients. Thus we have …
Published in Journal of Artificial Intelligence Research & Advances Read article
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DR. REVIVE: An AI-Powered Medical Recommendation System for Optimised Resources and Improved Patient Care
Abstract: Dr. Revive is an AI-powered medical recommendation system designed to enhance virtual healthcare interactions by connecting patients, doctors, and healthcare stakeholders. Leveraging advanced machine learning algorithms, it analyses user-reported symptoms to provide initial medical recommendations, serving as a reliable first point of guidance. With access to a comprehensive medical database, the platform delivers accurate and timely advice, empowering patients while supporting healthcare professionals with data-driven decision-making. By offering a complete …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 1–10 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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Impact on Mobility and Mortality in Minimally Invasive Surgeries
Abstract: Minimally invasive surgery (MIS) presents numerous advantages such as fewer complications, shorter hospital admissions, and reduced patient discomfort. This surgical method has progressed significantly, with laparoscopy being one of its earliest applications. Laparoscopy involves the insertion of miniature cameras and instruments through small incisions. Robotic-assisted surgery, another form of MIS, enhances surgical precision and offers a three-dimensional view. With technological developments, MIS has gained widespread acceptance among both surgeons and …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 3, 2025 · pp. 8–21 Read article
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Comparative Analysis of Data Augmentation Techniques in CNN-based Classification of Atelectasis
Abstract: This research delves into the critical issue of atelectasis, its causes, and potential complications if left untreated. Leveraging deep learning algorithms, particularly convolutional neural networks (CNN), the paper explores their application in medical image analysis, focusing on the detection of atelectasis using the “chestX-ray8” database. The study compares various data augmentation techniques for improved accuracy, showcasing the importance of augmentation in enhancing model generalization. Through meticulous experimentation and evaluation, the …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Neuro-Rehabilitation Reimagined: A Cross-Cultural Paradigm Integrating Immunotherapeutics and Multidimensional Analytics in Pediatric Cerebral Palsy
Abstract: Researchers performed multidimensional data analysis on the clinical records of 1,586 cerebral palsy pediatric patients to investigate the rehabilitative benefits of immunotherapy and the advantages of blending Traditional Chinese Medicine with Western treatments. A multi-center, prospective cohort study established a standardized system for data gathering that included clinical baseline databases along with treatment protocols and follow-up information. Baseline data analysis showed substantial patient diversity across clinical types and TCM syndromes …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 2, 2025 · pp. 67–84 Read article
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Multimodal Disease Detection Using Deep Learning
Abstract: Artificial Intelligence (AI) is playing an increasingly pivotal role in modern healthcare, particularly in improving the speed and accuracy of disease detection. With the evolution of Machine Learning (ML), Deep Learning (DL), and high-performance computing, AI-based solutions are now capable of processing extensive medical datasets, ranging from patient records to diagnostic images, with remarkable efficiency. These systems offer immense potential for early intervention, improved clinical decision-making, and alleviating pressure on …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 129–139 Read article
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Evaluation of Drug Utilization Patterns and Prescription Trends in Patients with Hypothyroidism and Hyperthyroidism in a Tertiary Care Hospital
Abstract: Background: Endocrine disorders affecting the thyroid gland represent some of the most frequently encountered conditions globally, necessitating prolonged therapeutic intervention and vigilant clinical surveillance. The evaluation of Drug utilization patterns (DUE) serves an essential function in examining prescriptive behaviours and promoting appropriate pharmaceutical management. Objective: To evaluate drug utilization patterns, prescribing trends, and rationality of therapy in patients with hypothyroidism and hyperthyroidism. Methods: A prospective, cross-sectional observational investigation was performed …
Published in Research and Reviews: A Journal of Medicine · Vol. 16, Issue 2, 2026 · pp. 1–5 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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Development of a Machine Learning and Artificial Intelligence Based Model Aimed at Forecasting the Prognostic Impact of C-Reactive Protein in Myocarditis
Abstract: The specific role of inflammation markers in myocarditis remains uncertain. We investigated the diagnostic and prognostic significance of C-reactive protein (CRP) levels at the initial diagnosis among myocarditis patients. Our retrospective study enrolled patients clinically suspected (CS) or biopsy-proven (BP) with myocarditis, with available CRP data at diagnosis. We collected patient information, including clinical, laboratory, and imaging findings at diagnosis and follow-up visits. We utilized machine learning methods, specifically random …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 2, 2024 · pp. 12–24 Read article
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Role of Artificial Intelligence in Simulation and Therapeutics in Neurodegenerative Diseases
Abstract: Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, etc., are a cause of significant mortality rates due to a lack of curative treatments and their complex nature. Traditional therapeutic methodologies have several disadvantages such as slow diagnosis and a lack of effective treatments. They mainly focused on the management of the disease rather than curing it. The integration of artificial intelligence in the simulation and therapeutics of neurodegenerative …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 19–29 Read article
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Proof-of-Minimum Privacy Leak Consensus Strategy in Blockchain
Abstract: In this study, we propose a novel consensus algorithm to preserve the security and privacy of a transaction. We propose a Proof-of-Minimum Privacy Leak consensus strategy. This means that the competing nodes which participate in the competition to mine the next block should give a proof of minimum privacy leak during its transaction. Only this proof will give highest votes to that node, and it will be elected as the …
Published in E-Commerce for Future & Trends Read article
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Pharmacovigilance: Enhancing Drug Safety Through Technology
Abstract: The research and practices surrounding the identification, evaluation, and avoidance of hazardous medication responses in people are known as pharmacovigilance. Pharmacovigilance has been defined as a kind of ongoing observation of side effects and other safety-related features of medications that have previously been introduced to the market. Pharmacovigilance has been shown to be crucial in promoting the sensible use of medications by disseminating knowledge about the negative effects that pharmaceuticals …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 38–44 Read article
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Advances in Simulation and Surgical Skill Training Evolution: Narrative Integrative Review
Abstract: Simulation-based education has emerged as a cornerstone of contemporary general surgery training, driven by increasing emphasis on patient safety, competency-based education, and rapid technological innovation. Traditional apprenticeship models, while foundational, are constrained by reduced operative exposure, work-hour limitations, and variability in clinical case mix. In this context, simulation provides a structured, reproducible, and safe environment for acquisition, assessment, and refinement of surgical skills across the training continuum. This narrative review …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 1, 2026 · pp. 7–13 Read article
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Navigating the Horizon: Current Trends in Elevating Quality Assurance in Clinical Research
Abstract: The landscape of clinical research quality management has evolved significantly in recent years, driven by stringent regulatory frameworks and globalization of trials. This evolution underscores the importance of integrating quality into all aspects of the clinical trial process from design to postresearch activities. Concepts such as Good Clinical Practice (GCP) and Quality by Design (QbD) are central to ensuring the reliability and accuracy of trial data while safeguarding patient safety …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 11, Issue 1, 2024 · pp. 1–8 Read article
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Graphs and Their Real-Life Applications in Pharmaceutical Research
Abstract: This study provides a comprehensive overview of the role of graphs in pharmacy research, emphasizing their significance as powerful tools for data visualization, interpretation, and communication. In the field of pharmacy, research often generates large volumes of complex data related to drug development, pharmacokinetics, pharmacodynamics, medication safety, and patient outcomes. Graphs serve as an essential medium to translate these data into accessible, interpretable, and actionable insights, supporting evidence-based practice and …
Published in Research & Reviews : Journal of Statistics · Vol. 14, Issue 3, 2025 · pp. 01–08 Read article
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Heart Attack Prediction Using Machine Learning
Abstract: Heart attacks have become a prevalent and serious condition in recent years due to a variety of causes. Numerous variables, including age, sex, fat, and others, can be used to predict it. In the current study, it was found that a data set with 13 parameters and 302 distinct data values, collected from a Kaggle dataset to assess patient condition, was covered. This article delves into the application of machine …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 1, Issue 1, 2023 · pp. 8–13 Read article
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Live Epidemiological Tracking of COVID-19 in Senegalese Participants of the Hajj
Abstract: Background: Since the COVID-19 outbreak, global efforts have focused on controlling the disease. However, intense cross border movements pose a risk for the emergence of new SARS-CoV-2 strains. A recent example is the detection of cases among the 2024 Senegalese pilgrims returning from Mecca, Saudi Arabia. Investigations of these cases have revealed genomic evolution of the virus. The lack of surveillance may lead to the emergence of high-threat strains. This …
Published in Recent Trends in Infectious Diseases · Vol. 2, Issue 2, 2025 · pp. 8–16 Read article