Search
122 articles for “Clinical data analysis”
-
A Study on Clinical Characteristics and The Impact Of Covid-19 In Hemodialysis Patients
Abstract: Background: The Corona Viruses Disease-19 pandemic has severely impacted Hemodialysis patients, who are vulnerable due to compromised immune systems and underlying comorbidities. Frequent Dialysis center visits increase their exposure risk to severe acute respiratory syndrome- Coronavirus Disease, and chronic inflammation, uremia, and immunosenescence may impair their immune response. Methods: This retrospective study included 60 Hemodialysis patients diagnosed with COVID-19 between January -July 2024. Data on demographics, clinical characteristics, laboratory results …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
-
A Study on the Comparative Changes in Nutritional Status in Follow-Up of End Stage Renal Disease Patients
Abstract: Dialysis Disequilibrium Syndrome (DDS) is a rare but serious neurological complication associated with hemodialysis, particularly during the initiation phase or in patients with high metabolic derangements. It is characterized by a range of neurological symptoms resulting from rapid shifts in plasma osmolality, leading to cerebral edema. Despite advancements in dialysis techniques, DDS continues to pose a clinical challenge due to its unpredictable nature and potential for severe outcomes. The present …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 16, Issue 1, 2026 · pp. 9–13 Read article
-
A Python-Based Investigation of Clinical Data and Ultrasound Images for PCOS Diagnosis
Abstract: PCOS is a common endocrine disorder that impacts women in their reproductive years characterized by irregular menstrual cycles, hyperandrogenism, and polycystic ovaries. The full diagnostic plan is mainly a combination of a pelvic ultrasound besides blood tests of specific parameters that indicate the presence of PCOS. Since PCOS is a hard-to-diagnose widespread hormonal disorder, blood tests, symptoms, and other parameters with the help of a computer can form a new …
Published in Research and Reviews : Journal of Computational Biology · Vol. 14, Issue 2, 2025 Read article
-
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
-
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
-
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
-
A Review on Lung Cancer Prediction Using Machine Learning
Abstract: Lung cancer continues to be a major contributor to cancer-related mortality across the globe. Timely diagnosis and reliable prediction models play a crucial role in enhancing treatment outcomes and survival rates for patients. The present study focuses on the utilization of machine learning (ML) methods for the prediction of lung cancer. Using datasets that incorporate clinical records, imaging modalities, and genetic profiles, the research assesses the predictive capabilities of multiple …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 3, 2025 · pp. 1–11 Read article
-
Molecular Mechanisms of Drug Metabolism in Anesthesia: A Pharmacogenomic Perspective
Abstract: Pharmacogenomics studies how a person’s genetic profile affects their reaction to drugs, which is vital in anesthesia. Anesthetic pharmacology depends significantly on drug metabolism, which involves complex biochemical processes that manage the absorption, distribution, metabolism, and excretion (ADME) of anesthetic drugs. The cytochrome P450 (CYP) enzyme family plays a critical role in the metabolism of various anesthetic drugs, with genetic polymorphisms leading to inter-individual variability in drug responses. Specific CYP …
Published in Research & Reviews: A Journal of Drug Formulation, Development and Production · Vol. 12, Issue 1, 2025 · pp. 90–95 Read article
-
Predictive Modeling of Polymer Composites for Medical Implants Using Artificial Intelligence Techniques
Abstract: The use of polymers in biomaterials was now key to designing the next generation of medical implants, which need to be strong and also compatible with living tissue. Tests for biocompatibility, such as those done in the laboratory and by doing experiments on animals, require much time and many resources, so the need for computer-based approaches becomes clear. An artificial intelligence approach was provided in this study to determine how …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 665–692 Read article
-
Patient Profile and Antimicrobial Susceptibility Testingin Clinical Isolates of Staphylococcus aureus
Abstract: INTRODUCTION: Staphylococcus aureus is a gram-positive bacterium capable of causing various infections, ranging from minor skin infections to serious bloodstream infections. The rise of methicillin-resistant S. aureus (MRSA) strains has made treating these infections more challenging, as MRSA is frequently resistant to several types of antibiotics.. OBJECTIVE: The aim of this study was to investigate the patient profile and antimicrobial susceptibility patterns of clinical isolates of S. aureus in a …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 14, Issue 2, 2024 · pp. 31–38 Read article
-
Predicting Multiple Diseases Using Machine Learning: A Data-Driven Approach
Abstract: The increasing prevalence of chronic and life-threatening diseases highlights the need for innovative healthcare solutions that enable early detection and proactive management. The Multiple Disease Prediction Platform is a web-based system utilizing machine learning (ML) and deep learning (DL) algorithms to analyze user-inputted health data, generating real-time predictions of potential health risks. By leveraging Python’s Streamlit library, the platform provides an interactive and accessible diagnostic experience, eliminating the need for …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 2, 2025 · pp. 16–35 Read article
-
Air Pollution and Immune Disorders in Women from Urban Punjab: A Clinical and Epidemiological Study
Abstract: Background: Urban Punjab, particularly cities like Ludhiana, Amritsar, and Jalandhar, experiences some of the highest air pollution levels in India due to industrial activity, vehicular emissions, and agricultural practices. Despite this, gender-specific health impacts—especially related to immune function—remain inadequately studied. Objective of the study is to investigate the relationship between air pollution exposure and immune-related disorders in women residing in urban Punjab. A cross-sectional study was conducted from 2022 to …
Published in International Journal of Environmental Noise and Pollution Control · Vol. 3, Issue 1, 2025 · pp. 36–40 Read article
-
High-Definition Electroencephalography: A New Horizon in Neurological Pathology Research
Abstract: The advent of high-density electroencephalography (HD-EEG) has catalyzed a paradigm shift in the exploration of neurological pathologies. This editorial underscore its transformative potential in elucidating brain dynamics and refining diagnostic approaches for a spectrum of conditions, spanning from epilepsy and dementia to cognitive impairments in preterm infants. Our objective is to optimize the utility of HD-EEG by emphasizing the imperative for methodological homogenization and fostering collaborative endeavors. The remarkable spatial …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 15–21 Read article
-
Evaluating the Role of Platelet Indices, with a Focus on Immature Platelet Fraction (IPF), in Differentiating Hyper-Destructive and Hypo-Productive Thrombocytopenia: A Study from Ludhiana, Punjab, India
Abstract: Background: Thrombocytopenia, characterized by a reduction in platelet count, is commonly observed in clinical settings. Its etiology can be broadly classified into hyper-destructive thrombocytopenia, where platelets are destroyed at an accelerated rate, and hypo-productive thrombocytopenia, where platelet production is impaired. Differentiating between these two causes is essential for effective management. The Immature Platelet Fraction (IPF) has emerged as a promising non-invasive diagnostic tool to distinguish these causes. Objectives: The primary …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 2, 2025 Read article
-
Post Pandemic Cardiac Prediction: Analysing Heart Attack Mortality Rate In Vaccinated Adults
Abstract: Heart disease has emerged as a prominent contributor to global mortality rates. Discovered it early and providing timely management can significantly reduce the incidence of heart failures, death rates, and diagnostic costs associated with heart disease. In this study, we propose employing notification system to assess the risk of heart disease and explore potential associations between vaccination status and mortality rates due to heart attack among adult populations in the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 2, 2024 · pp. 45–51 Read article
-
Early Alzheimer's Disease Detection Using Deep Ensemble Learning and MRI Image Analysis
Abstract: Early detection of Alzheimer's disease (AD) is crucial to slowing cognitive decline and enabling timely clinical interventions. Traditional diagnostic methods, including cognitive tests and single-model classifiers, have limited sensitivity during early stages of the disease. This paper presents a deep ensemble learning approach that integrates multiple convolutional neural networks (CNNs) for accurate Alzheimer's disease detection using structural Magnetic Resonance Imaging (MRI) data. The proposed framework utilizes ResNet50, VGG16, and DenseNet121 …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
-
Artificial Intelligence in Early Diagnosis and Personalized Treatment of Alzheimer’s Disease
Abstract: Artificial intelligence (AI) has become a disruptive technology in the medical care industry, with potential solutions to early diagnosis and customized treatment of Alzheimer’s disease (AD), a progressive neurodegenerative disease and the most prevalent cause of dementia globally. Conventional diagnostic techniques, such as cognitive, neuroimaging and biomarker techniques, are usually limited in the ability to detect disease at its most susceptible stage when treatment interventions are most effective. The recent …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 · pp. 15–27 Read article
-
A Comparative Study of the Structure-Property Relationships in CAD/CAM Milled vs. 3D-Printed High-Performance Polymers: Impact of Molecular Orientation on Abrasive Wear
Abstract: Background: The transition from subtractive to additive manufacturing in prosthetic dentistry has introduced significant variations in the macromolecular architecture of high-performance polymers. While CAD/CAM milling utilizes high-density, industrially polymerized blocks, 3D printing (Additive Manufacturing) relies on layer-by-layer deposition, which may induce anisotropic molecular orientation. This retrospective study investigates how these distinct manufacturing "thermal histories" influence the long-term abrasive wear resistance of PEEK and PEKK restorations.Materials and Methods: Data were retrospectively …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 Read article
-
Comparative Analysis and Future Research Directions in AI in Healthcare: Medical Imaging and Diagnostics
Abstract: Artificial intelligence (AI) is reshaping healthcare, particularly in the areas of medical imaging and diagnostic practice. By using advanced techniques like machine learning and deep learning, AI systems help improve the accuracy, speed, and effectiveness of identifying diseases and analyzing medical images. This paper provides a comprehensive overview of the application of artificial intelligence in medical imaging and highlights its growing importance in clinical diagnostics. It discusses how AI-based systems …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 4, Issue 1, 2026 · pp. 8–13 Read article
-
Early Alzheimer’s Disease Prediction Using Vision Transformers and Attention-Guided MRI Analysis
Abstract: Alzheimer’s Disease (AD) continues to be a major global health concern, with early detection being crucial for effective intervention. While conventional machine learning and convolutional neural network (CNN) approaches have made notable progress in automated AD diagnosis using MRI data, they often struggle with capturing long-range dependencies and maintaining spatial contextual awareness. In this research, we propose a novel framework using Vision Transformers (ViTs) for early Alzheimer’s prediction from 3D …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 30–40 Read article