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357 articles for “Patient data”
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Impact of Training Program on Recent Innovations in Oncology Among Nursing Professionals
Abstract: Introduction: In recent years, there have been significant advancements and trends in the field of oncology treatment in India. This study aimed to evaluate impact of training program on knowledge regarding recent innovations in oncology among nursing professionals. After ethical approval, a pre-experimental, one group pretest- post-test design was used to conduct this research at anursing college of Punjab. Methods: The sample was selected using the total enumerative sampling technique. …
Published in International Journal of Oncological Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 9–14 Read article
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Patient Profile and Antimicrobial Susceptibility Testing of Clinically Isolates In E. coli
Abstract: Escherichia coli, commonly known as E. coli, is a prevalent bacterium capable of causing infections in humans. The development of antimicrobial resistance in E. coli poses a significant public health issue. This study aimed to determine the patient profile and antimicrobial susceptibility patterns of clinically isolated E. coli. A retrospective study was carried out on E. coli samples collected from clinical specimens within a hospital environment. Patient profiles, including age, …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 14, Issue 1, 2024 · pp. 32–47 Read article
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The Concept of Guillain-Barré Syndrome (GBS) in Unani Medicine and the Potential Role of Unani Pharmacology in Its Management
Abstract: Introduction: Guillain–Barré Syndrome (GBS) is an autoimmune neurological disorder characterized by progressive muscle weakness and paralysis due to immune-mediated damage to the peripheral nervous system. Conventional treatments focus on immunotherapy and supportive care, but alternative approaches, such as Unani Medicine offer promising holistic management strategies. Unani Medicine attributes GBS to humoral imbalance, particularly an excess of Balgham (Phlegm) affecting nerve function, leading to weakness and dysfunction. Objective: This study aims …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 14, Issue 2, 2025 · pp. 32–52 Read article
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A Systematic Review of the Herbal Medicinal Plants With Anti-Obesity Potential
Abstract: Obesity is a chronic, multifactorial metabolic condition characterized by abnormal fat accumulation. It is mainly driven by the intricate influence of genetic, environmental, hormonal, metabolic and lifestyle determinants. The burden of obesity has risen considerably over the past few years, making it one of the major health concerns in both developed and developing countries alike. The rapid increase globally in obesity prevalence is linked with numerous health complications such as …
Published in Research & Reviews : Journal of Herbal Science · Vol. 15, Issue 2, 2026 Read article
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Review article on Quality Control in Clinical Trials
Abstract: Quality control (QC) is a critical component in the conduct of clinical trials, ensuring the accuracy, reliability, and credibility of data collected throughout the study. It encompasses a systematic set of procedures designed to monitor trial conduct and data integrity, thus safeguarding the rights, safety, and well-being of participants. This review explores the principles, implementation, and evolving practices of quality control in clinical trials, highlighting its importance across all phases …
Published in Research & Reviews: A Journal of Drug Design & Discovery · Vol. 12, Issue 3, 2025 · pp. 01–07 Read article
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Calorie Measurement and Food Recognition Using Machine Learning
Abstract: Nowadays, all over the world most people are suffering from different types of diseases or obesity. This is because of bad food habits or eating food without knowing the calorie and other sources from the foods. Precise techniques for gauging food and energy consumption play a vital role in addressing obesity. Offering users or patients accessible and smart solutions to assess their food intake and gather dietary information constitute valuable …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 1–9 Read article
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An Evaluation of the Impact of a Nurse-Led Program on Knowledge and Practices Related to Needle Stick Injury Prevention Among 2nd Year B.Sc. Nursing Students at the College of Nursing, PT. B.D. Sharma PGIMS, Rohtak
Abstract: Healthcare workers and nursing students frequently face accidental occupational exposures while caring for patients, with needle stick injuries being the most common form of exposure in healthcare settings. These injuries pose a significant risk of infections. This study aimed to evaluate the awareness and practices related to the prevention of needle stick injuries among second-year B.Sc. Nursing students, assess the effectiveness of a nurse-led intervention in enhancing their knowledge and …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 3, Issue 1, 2025 · pp. 28–66 Read article
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Comprehensive Analysis of MRSA Peptides Via Maldi
Abstract: The present study employed Matrix-Assisted Laser Desorption/Ionization Time-of-Flight mass spectrometry to analyze methicillin-resistant Staphylococcus aureus peptides, focusing on various parameters associated with mass-to-charge (m/z) values. Through systematic data collection and analysis, including time, intensity, signal-to-noise ratios, quality factors, resolutions, areas under the peaks, relative intensities, full widths at half maximum, Chi-squared values, and background peaks, comprehensive insights into the spectral characteristics of methicillin-resistant Staphylococcus aureus peptides were obtained. Methicillin-resistant Staphylococcus …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 15, Issue 2, 2024 · pp. 98–101 Read article
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Detection and Classification of Diabetic Retinopathy Using Deep Learning Techniques
Abstract: This project delves into the evaluation of three prominent deep learning architectures Basic CNN, ResNet, and DenseNet for their efficacy in detecting diabetic retinopathy from retinal images. Utilizing a diverse dataset, the study employs standard deep learning frameworks to train and validate each model. The focus extends to exploring the potential benefits of transfer learning on a limited dataset. Evaluation metrics like specificity, sensitivity, and accuracy are employed for a …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 64–69 Read article
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Parkinson’s Disease Detection on Spiral Images Using CNN with Meta-Classifiers
Abstract: In this work, we provide a detailed method for identifying Parkinson’s Disease (PD) by integrating Convolutional Neural Network (CNN) and meta-classifiers. Through the utilization of a varied dataset consisting of handwritten spiral images, our methodology demonstrates commendable accuracy across a range of models. Specifically, our CNN model with meta-classifiers surpasses alternative approaches, achieving an impressive accuracy rate of 95.07%. By utilizing pre-established VGG16 and ResNet50 architectures as bases, the region-based …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 1, 2025 · pp. 55–66 Read article
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Radio Frequency Next-Generation Advances
Abstract: Radio frequency (RF) technology is a key enabler for modern wireless communications, driving the evolution of telecommunications, healthcare, aerospace, defence and the Internet of Things (IoT). Faster, more reliable and energy-efficient communication systems have been developed at a rapid pace due to recent discoveries in RF engineering. This article discusses novel advancements in RF technologies including enhanced antenna design, millimeter-wave communication, software defined radio, smart spectrum management, and RF-based sensor …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 1, 2026 Read article
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A Study on Cancer Related Fatigue and Quality of Life (QOL) among Women Undergoing Treatment for Various Cancers in Selected Tertiary Care Hospitals of Ludhiana, Punjab
Abstract: Cancer is a collection of illnesses marked by irregular cell proliferation that has the potential to infiltrate or metastasize to different areas of the body. Gynecological cancer specifically refers to the abnormal cell growth in the female reproductive tract, including various organs such as the endometrium, fallopian tubes, ovaries, uterus, cervix, vagina, and breast. These cancer cells have a tendency to multiply uncontrollably. The majority of individuals diagnosed with cancer …
Published in International Journal of Oncological Nursing and Practices · Vol. 1, Issue 1, 2023 · pp. 6–11 Read article
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Design and Fabrication of a 3D-Printed Femur Model: Insights into Mechanical Properties and Implant Research
Abstract: This study is an attempt to analyse the 3D printing of the female femur model of the central India region and provides ample suggestions for bone implant research. This article discusses the design development and experimental validation of finite element analysis (FEA) results with the 3D-printed bone model. Using CT scan data, the FE analysis is executed on a real femur bone of a 25-year-old female of 52 kg weight …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 329–338 Read article
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Advanced Deep Learning Techniques for Sickle Cell Anaemia Detection
Abstract: Sickle Cell Anemia (SCA) is a prevalent genetic blood disorder characterized by the presence of abnormal hemoglobin, resulting in the distinctive sickle shape of red blood cells. Timely and accurate identification of Sickle Cell Anemia (SCA) is essential for effective management and treatment. This study presents a new method that utilizes Convolutional Neural Networks (CNNs), a deep learning model particularly effective for image analysis. The process involves using microscopic images …
Published in Research and Reviews: A Journal of Medicine · Vol. 14, Issue 3, 2024 · pp. 9–15 Read article
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Adoption of Artificial Intelligence in Periodontal Diagnostics: Awareness, Confidence, and Barriers Among Dental Practitioners in India
Abstract: AI has emerged as a transformative tool in healthcare, including periodontics, where it aids in diagnosing periodontal diseases, assessing bone loss, and predicting disease progression. Despite its potential, the adoption of AI in dentistry, particularly in India, remains limited. This study aimed to evaluate the awareness, confidence, and willingness of dental practitioners to adopt AI-based tools in periodontal diagnostics. A cross-sectional survey was conducted among 106 dental practitioners, including general …
Published in Research and Reviews: A Journal of Dentistry · Vol. 16, Issue 3, 2025 · pp. 27–38 Read article
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Descriptive Study to Evaluate Attitudes Toward Teenage Pregnancy Among Nursing Students in a Selected College in Virudhunagar
Abstract: This study aimed to explore the attitudes of nursing students toward teenage pregnancy, focusing on a specific college in Virudhunagar. A purposive sampling technique was employed to select 50 participants using non-probability sampling methods. Data were gathered through a structured questionnaire based on a 5-point Likert scale, comprising 10 statements with response options ranging from "strongly disagree" to "strongly agree." The data collected were systematically organized, tabulated, and analyzed using …
Published in International Journal of Midwifery Nursing And Practices · Vol. 2, Issue 2, 2024 · pp. 22–27 Read article
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Breast Cancer Detection Using Machine Learning: A Comparative Analysis of Supervised Learning Algorithms
Abstract: Globally, breast cancer remains a predominant cause of mortality among women, highlighting the urgent need for timely and precise diagnostic approaches. This research explores the application of machine learning algorithms—including Logistic Regression, SVM, Naïve Bayes, KNN, and Random Forest—on the Wisconsin Breast Cancer Dataset for effective tumor classification. Key pre-processing steps such as missing value handling, feature scaling, and dimensionality reduction were employed to improve model performance. The study evaluated …
Published in Research & Reviews: A Journal of Bioinformatics · Vol. 12, Issue 3, 2025 · pp. 46–52 Read article
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Pneumonia Identification Using Explainable Artificial Intelligence
Abstract: Pneumonia, including tuberculosis (TB), remains one of the leading causes of death worldwide, especially in regions where access to healthcare is limited. Early and accurate diagnosis is critical for effective treatment and better patient outcomes, but traditional methods are time-consuming and require specialized expertise. This study explores the use of advanced deep learning models VGG16, VGG19, and ResNet50 to detect pneumonia and TB from chest X-ray images. By leveraging transfer …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 01–11 Read article
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A Study to Assess the Effectiveness of Body Mechanics Training Programme on Reducing Low Back Pain Among Nursing Officers Working in Selected Hospitals, Bangalore
Abstract: Background: Low Back Pain (LBP) is a common work related injury and costly problem among the nursing profession. Numerous studies indicate a greater occurrence of back pain and work-related back injuries among nursing officers in comparison to other occupations. Prevention of LBP is a very important technique to maintain proper body mechanics. This study aimed to assess the effectiveness of body mechanics training programme on reducing low back pain among …
Published in International Journal of Orthopedic Nursing and Practices · Vol. 2, Issue 1, 2024 · pp. 29–62 Read article
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Comparative Proteomics: From Cell Lines to Clinical Samples
Abstract: Comparative proteomics is a powerful tool for understanding the molecular differences between various biological samples. It entails identifying and measuring proteins in complex biological samples to assess their abundance, modifications, and interactions under various conditions. This approach plays a crucial role in advancing biomedical research, especially in disease understanding, biomarker discovery, and therapeutic development. While cell lines are widely used for proteomic studies due to their controlled environments and reproducibility, …
Published in Research and Reviews : Journal of Computational Biology · Vol. 13, Issue 3, 2024 · pp. 30–34 Read article