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298 articles for “Clinical Data”
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Brain Tumor Detection Using RestNet50 Architecture
Abstract: This paper presents a novel deep learning model for brain tumor diagnosis from MRI scans on the basis of ResNet50 with some modifications. Optimizing the modified layers and pre-trained ResNet50 for improved diagnostic accuracy and reliability in real-world clinical settings is one of the key contributions of this paper. The model was trained on an extremely well-balanced data of 2,577 MRI scans, which were split equally among the tumor and …
Published in Current Trends in Signal Processing · Vol. 15, Issue 2, 2025 · pp. 1–13 Read article
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Pathophysiology Reimagined: Integrating Systems Biology and AI for Disease Understanding
Abstract: Pathophysiology, the study of disease mechanisms at molecular, cellular, and systemic levels, has traditionally relied on reductionist approaches that often fail to capture the complex, dynamic, and interconnected nature of biological systems. Diseases such as cancer, neurodegenerative disorders, and infectious diseases arise from intricate interactions among genetic, epigenetic, metabolic, and environmental factors, necessitating integrative, data-driven methodologies for a deeper understanding. Systems biology has emerged as a powerful approach by leveraging …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 2, 2025 · pp. 63–71 Read article
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Effect of Snehpana (Lipid Based Drug Delivery System) with Shatpala Ghrit in Non-Alcholic Fatty Liver Diseases
Abstract: Among all the Drug Delivery Systems, Snehpana (~Lipid Based Drug Delivery System) is being widely used because this facilitates uniform distribution and absorption of fat and water-soluble chemical constituents. Due to their effective size-dependent properties and challenges related to the solubility and bioavailability of water-soluble drugs, this system holds a significant advantage. Numerous studies have highlighted the potential of lipid-based formulations in managing chronic and life-threatening diseases. Shatpala ghrit (SG) …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 12, Issue 1, 2025 · pp. 1–11 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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Clinical Profile of Dengue Patients who had a Prior Infection with the Covid 19 Virus in a Tertiary Care Centre
Abstract: This cross-sectional analytical study conducted in a tertiary care center aims to investigate the clinical profile of Dengue virus-infected patients with a prior history of COVID-19 within the last three years. Dengue, a prevalent tropical disease, ranges from mild fever to severe conditions like hemorrhagic fever and shock syndrome. The study utilizes the World Health Organization's 2009 classification for Dengue and delineates the febrile, critical, and recovery phases of infection. …
Published in Recent Trends in Infectious Diseases · Vol. 1, Issue 1, 2024 · pp. 34–38 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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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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A Systematic Review on Leukemia Detection and Classification Techniques Using Gene Expression
Abstract: Early diagnosis of genetic diseases is crucial for effective treatment, especially in the case of Leukemia, a type of blood cancer characterized by abnormal proliferation of white blood cells. This paper presents a systematic review of recent computational techniques for the detection and classification of Leukemia using gene expression data obtained from DNA microarray analysis. The study explores diverse methodologies including machine learning (ML), deep learning (DL), and bio-inspired algorithms …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 3, Issue 2, 2025 Read article
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A Study on Smart Healthcare Innovations
Abstract: The desire for effective, patient-centred solutions and the rapid growth of technology are driving forces in the healthcare industry. The term "smart healthcare innovation" refers to a broad category of approaches, tools, and procedures that are intended to improve patient outcomes, optimize resource use, and enhance overall healthcare delivery. These innovations integrate cutting-edge technologies such as artificial intelligence (AI), the Internet of Things (IoT), wearable devices, big data analytics, and …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 · pp. 63–68 Read article
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Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 Read article
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A Review on Transforming Patient Pathways: The Impact of Pharmaceutical Software on Drug Manufacturing and Safety Monitoring
Abstract: The development, production, and safety monitoring of pharmaceuticals are being revolutionized by incorporating digital technologies. Throughout drug lifecycles, pharmaceutical software which includes cloud-based systems, automation, data analytics, and artificial intelligence (AI) has emerged behind efficiency and innovation. Real-time monitoring, predictive maintenance, and process optimization are made possible in manufacturing by software tools like Digital Twins, Manufacturing Execution Systems (MES), and Quality Management Systems (QMS). These technologies improve batch consistency, lower …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 40–46 Read article
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Artificial Intelligence in intra operative and peri operative management of major oral and maxillofacial surgeries
Abstract: Artificial Intelligence and virtual reality are becoming a part of everyday life and are enhancing our quality of life extensively. It is only natural that the same shall be used in surgery also. The existing body of literature on artificial intelligence (AI) and its integration into various surgical specialties has been extensively reviewed and discussed in this article. These insights, though derived from broader surgical domains, can be effectively translated …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 2, 2025 · pp. 1–5 Read article
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Quality of Sleep Among Patients with Chronic Renal Failure
Abstract: Renal failure is the partial or complete impairment of kidney function. Inability to eliminate metabolic waste products and water, along with functional disruptions in all bodily systems, result in the condition known as renal failure. Renal failure can be categorized as either acute or chronic. Chronic renal failure refers to the gradual and irreversible deterioration of the nephrons in both kidneys. It is characterized by either kidney damage or a …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 1, Issue 1, 2023 · pp. 22–28 Read article
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The Contribution of A. I. in Pharmaceutical Software
Abstract: The integration of Artificial Intelligence (AI) in pharmaceutical software has significantly transformed drug development, regulatory processes, and clinical management. AI-powered tools are revolutionizing data analysis, predictive modeling, and decision-making, enhancing the efficiency and accuracy of drug discovery and development. This article explores the multifaceted contributions of AI to pharmaceutical software, including its applications in drug screening, personalized medicine, clinical trial optimization, and regulatory compliance. Additionally, we examine how AI is …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 1–10 Read article
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IoT-Enabled Flexible Polymer Sensors for On-Body Health Monitoring and Real-Time Data Transmission
Abstract: Wearable health monitoring systems have grown increasingly vital in shifting care beyond clinical settings, yet many existing technologies remain hamstrung by rigid substrates and unreliable data streaming, impeding continuous and comfortable physiological assessment. Despite advances in flexible materials, most current sensor platforms suffer from limited mechanical endurance, signal instability under dynamic conditions, or an inability to sustain real-time wireless transmission. This work addresses those deficiencies by introducing a fully integrated, …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 188–200 Read article
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Adaptive Drift Correction in Polymer-Based Wearable Biosensors via Data-Driven Signal Modeling
Abstract: Polymer-based wearable biosensors have emerged as a promising technology for continuous health monitoring due to their mechanical flexibility, biocompatibility, and suitability for long-term physiological interfacing. However, prolonged exposure to biofluids, environmental variability, and mechanical deformation introduces signal drift, which significantly degrades measurement accuracy and limits clinical reliability. This paper presents a data-driven methodology for compensating signal drift in polymer-based wearable biosensors using adaptive signal processing and machine learning techniques. The …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 131–139 Read article
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Advances in Biological Systems Modeling for Predicting Drug Effects in Chronic Disease
Abstract: Biological systems modeling has emerged as a promising tool for understanding and predicting the effects of drugs in the treatment of chronic diseases. Chronic diseases, such as diabetes, cardiovascular diseases, and neurodegenerative disorders pose significant challenges to traditional drug development due to their complex, multifactorial nature. Systems biology approaches, which integrate computational modeling with experimental data, provide a holistic view of disease mechanisms and treatment responses. This review explores recent …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 1, 2025 · pp. 17–22 Read article
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Comparative Analysis of the Structural Integrity and Dimensional Stability of Additively Manufactured Biopolymers vs. Thermoformed PETG: A 1-Year Retrospective Study on Polymer Performance in Orthodontic Applications
Abstract: Objective: This study aimed to evaluate the long-term dimensional accuracy and structural performance of direct 3D-printed biopolymers compared to conventional vacuum-formed Polyethylene Terephthalate Glycol (PETG) composites. The investigation focused on how different polymer processing methods (additive manufacturing vs. thermoforming) influence material thinning and resistance to occlusal stress. Methods: A retrospective analysis was conducted on 60 cases (n = 60) of post-orthodontic maintenance. The sample was divided into two cohorts: Group …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 140–146 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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Exploring the Development of AI Models Using Open-Source Tools to Predict Patient Outcomes and Optimize Treatment Plans
Abstract: Integrating artificial intelligence (AI) into healthcare offers a transformative opportunity to enhance patient care and clinical decision-making. Through the use of predictive analytics, AI can significantly enhance the accuracy of outcome predictions and assist in developing personalized treatment plans that cater to each patient’s specific needs. This paper delves into the development of AI models using open-source tools, which are increasingly favored for their accessibility, collaborative nature, and capacity for …
Published in Journal of Open Source Developments · Vol. 11, Issue 3, 2024 · pp. 37–49 Read article