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357 articles for “Patient data”
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Impact of Spinal Cord Injury on Body Composition and Weight
Abstract: Weight gain is a common consequence of spinal cord injury (SCI), often resulting from decreased physical activity, metabolic alterations, and changes in body composition. This study aimed to assess post-injury weight changes among individuals with SCI. Data was obtained using a multistage random sampling method, utilizing a patient questionnaire administered to 28 individuals diagnosed with SCI. Participants’ baseline weights were compared with their recorded weights at follow-up. The mean initial …
Published in Research and Reviews : Journal of Surgery · Vol. 15, Issue 1, 2026 · pp. 19–34 Read article
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Orthostride: An Internet of Medical Things-Enabled Smart Rehabilitation Footwear System for Real-Time Monitor
Abstract: The orthopedic rehabilitation goal of controlled weight bearing, a stable gait progression, and early recognition of hazardous situations for safe mobility is traditionally met through time, scheduled in-clinic observation and clinician induction, and patient report. In this work, Orthostride, a smart rehabilitation footwear prototype intended to augment postoperative and injury-related lower extremity restoration through continuous sensing, embedded decision logic, local feedback, and remote telemetry, is proposed. This system incorporates force …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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A Study on the Prevalence and Causative Factors of Anemia in Patients Undergoing Maintenance Hemodialysis
Abstract: Anemia is a common and serious issue in individuals with chronic kidney disease (CKD) who are on maintenance hemodialysis (MHD), greatly affecting their overall health and quality of life (QoL). Despite advancements in treatment, anemia remains a challenging issue in this population. This study investigates the prevalence of anemia and identifies the contributing factors in CKD patients on MHD with the aim of enhancing clinical management strategies. This study focused …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 1, 2024 · pp. 73–89 Read article
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Evaluation of Patient-Specific Quality Assurance for RapidArc Treatment Delivery Using Dose Volume Histogram
Abstract: This study aims to evaluate the application of dose volume histogram (DVH) metrics within the patient-specific quality assurance (PSQA) protocol in various sites for RapidArc treatment delivery. Forty patients were included in this study, of which twenty each Head and Neck (H&N) and Pelvis Rapid Arc plans were evaluated. Octavius 4D 1500 detector array with vented parallel plate ion chambers was used for this study, which reconstruct the pre-treatment measured …
Published in Journal of Polymer & Composites · Vol. 11, Issue 7, 2023 · pp. 14–22 Read article
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Medical Science in the Digital Era: A Comprehensive Study on Computing in Healthcare
Abstract: Adding computers to medical science has changed how healthcare is delivered, how research is done, and how well patients do. This article talks about the many ways that computer technology is used in modern medicine, such as for diagnostic imaging, electronic health records (EHRs), telemedicine, surgical robotics, and research that is based on data. Improvements in artificial intelligence (AI) and machine learning have made it possible to make more accurate …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 Read article
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Assessment of Quality of Life and Coping Strategies Used by Amputated Patients Attending Orthopedics OPD to Provide Rehabilitation Program: A Descriptive Study
Abstract: Introduction: Amputation is defined as the surgical removal of a body appendage such as limbs. It has a profound social, economic, physical and psychological impact on patients. Objectives of the study: To assess the quality of life and coping-strategies used by an amputated patient and to determine an association between the quality of life and coping-strategies with selected socio-demographic variables at Pt. B. D. Sharma, PGIMS, Rohtak. Material and Method: …
Published in International Journal of Orthopedic Nursing and Practices · Vol. 3, Issue 1, 2025 · pp. 23–39 Read article
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A Hybrid Machine Learning Approach for Cardiovascular Disease Prediction
Abstract: Heart disease ranks among the top causes of death globally. Accurately predicting cardiovascular conditions has become a key challenge in the realm of clinical data analysis. It has been shown that machine learning is an effective means of assisting with predicting and decision-making based on the large volume of data produced by the medical industry. In this study, we describe a unique approach that increases the prediction accuracy of heart-related …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 1, 2025 · pp. 69–75 Read article
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An Evidence Based Analytical Study on Capability of ChatGPT in Advanced AI Based Patient Drug Counseling
Abstract: The application of ChatGPT in providing drug counseling to patients offers the best approach to enhancing policies of healthcare support in decision-making. Aim and Objectives: The present study mainly involves an evaluation of the capability of ChatGPT in the management of drug counseling among patients suffering from various metabolic disorders. Methodology: The present study was a community-based interventional study conducted for a period of 12 months from October 2023 to …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 15, Issue 1, 2025 · pp. 8–13 Read article
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SGLT2 Inhibitors in Heart Failure and Chronic Kidney Disease: Expanding Therapeutic Horizons beyond Glycemic Control
Abstract: Heart failure (HF) and chronic kidney disease (CKD) are closely related clinical diseases that significantly increase morbidity and death worldwide. The co-occurrence of both conditions is frequently referred to as the "cardio-renal syndrome," in which the failure of one organ hastens the decline of the other. The original purpose of sodium–glucose cotransporter-2 (SGLT2) inhibitors was to treat type 2 diabetic mellitus (T2DM) by reducing blood sugar levels. Nevertheless, new data …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 2, 2026 Read article
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Uttarabasti in Female Infertility: A Retrospective Analysis of Clinical Outcomes and Safety Profile
Abstract: Background: Uttarabasti (UB) is a specialized Panchakarma procedure involving intrauterine instillation of medicated Sneha, classically indicated in Yonivyapad and Vandhyatwa. It facilitates targeted local drug delivery, bypassing gastrointestinal metabolism and enabling direct therapeutic action at the uterine level. In Ayurvedic understanding, UB achieves Garbhashaya Shuddhi and Apana Vata Anulomana — the two primary pathological corrections considered essential in Vandhyatwa. Infertility affects an estimated 10–15% of couples globally, with a substantial …
Published in Research and Reviews : A Journal of Ayurvedic Science, Yoga and Naturopathy · Vol. 13, Issue 2, 2026 Read article
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AI Driven IoT Based Decision Making System for Brain wave study: KSK approach for Brain wave study
Abstract: The rapid convergence of Internet of Things (IoT) architectures and deep learning has unlocked unprecedented potential for real-time neuro-diagnostic monitoring. This paper presents a novel framework for an AI-driven IoT ecosystem designed to capture, transmit, and interpret human electroencephalography (EEG) signals with minimal latency. Traditional brain-computer interface (BCI) studies are often constrained by localized computing power and the high dimensionality of neural data. Our proposed architecture integrates low-power EEG sensors …
Published in International Journal of Brain Sciences · Vol. 3, Issue 2, 2026 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Emerging Digital Trends in Virology Software: Optimizing Viral Discovery, Surveillance,and Patient Management.
Abstract: Virology and antiviral therapeutics are being reshaped by rapid advances in computational tools, automation platforms, and virus-focused digital health applications. Software systems now span the entire virology value chain, from in silico viral target identification and antigen design, to AI-supported clinical trial management for vaccines and antivirals, to post-marketing pharmacovigilance and patient-facing mobile tools. This review examines current and emerging software trends relevant to virus studies, emphasizing applications in viral …
Published in International Journal of Virus Studies · Vol. 3, Issue 1, 2026 · pp. 29–38 Read article
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A Review on Applications of Artificial Intelligence (AI) in Parkinsons’s Disease Diagnosis and Treatment and Its Future Challenges
Abstract: Parkinson’s disease (PD) is a long-term, progressive neurodegenerative disorder that mainly occurs in people older than 60 years, affecting nearly 1% of this population. It is chiefly marked by the loss of dopaminergic neurons in the substantia nigra, a crucial brain region responsible for controlling motor functions. The resultant dopamine deficiency significantly disrupts motor control, manifesting in clinical symptoms such as tremors, bradykinesia, muscle rigidity, and postural instability. While PD …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 · pp. 1–15 Read article
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Pharmacovigilance And Drug-Induced Toxicities: A Clinical Perspective
Abstract: Pharmacovigilance, which aims to detect, assess, and prevent medication-induced toxicities and adverse drug reactions (ADRs), is a crucial part of healthcare. This study examines the several kinds of drug-induced toxicities, such as idiosyncratic, dose-dependent, and allergic reactions, and emphasizes the function of clinical pharmacists in the tracking and treatment of these illnesses. Pharmacovigilance systems are crucial because they can identify and handle drug-related safety issues that might not surface during …
Published in Research and Reviews: A Journal of Toxicology · Vol. 14, Issue 3, 2024 · pp. 17–30 Read article
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Revolutionizing Healthcare: AI in Drug Discovery and Pharmacy Practices
Abstract: Artificial intelligence (AI) has emerged as a revolutionary element across numerous sectors, especially in healthcare and pharmacy. AI systems that can execute functions typically necessitating human intelligence, such as learning, problem-solving, and speech recognition, are poised to transform drug discovery, enhance patient care, and reshape pharmacy practices. AI can help discover drugs with predicting interactions with drug destinations, virtual screening, drug reuse, and drugs that accelerate the development of effective …
Published in Research and Reviews: A Journal of Pharmaceutical Science · Vol. 16, Issue 1, 2025 · pp. 94–100 Read article
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Leveraging AI and Machine Learning for Early Prediction and Prevention of Non- Communicable Diseases in Resource-Limited Settings
Abstract: Populations in these regions face persistent structural barriers, such as underdeveloped healthcare infrastructure, shortages of trained health professionals, and fragmented or incomplete health information systems. These limitations delay timely diagnosis, restrict access to preventive care, and compromise effective disease management. In recent years, rapid progress in artificial intelligence (AI) and machine learning (ML) has opened promising avenues to mitigate these challenges. Practical applications already emerging include mobile health platforms for …
Published in Journal of AYUSH: Ayurveda, Yoga, Unani, Siddha and Homeopathy · Vol. 15, Issue 1, 2026 · pp. 9–15 Read article
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Early Detection of Alzheimer’s Disease Using Machine Learning Techniques
Abstract: Alzheimer's Disease (AD) is a progressive neurodegenerative condition impacting a large global population. Detecting AD early is critical for timely intervention and effective management. Conventional diagnostic approaches involve cognitive assessments and neuroimaging, which are often lengthy, costly, and prone to human error. In this paper, we propose a novel approach for early detection of AD using machine learning techniques applied to multimodal data, including neuroimaging, cognitive assessments, and biomarkers. Our …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 14, Issue 2, 2024 · pp. 32–43 Read article
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Assessing Supportive Care Needs Among Breast Cancer Survivors: A Cross-Sectional Study
Abstract: Breast cancer poses a significant global health challenge and ranks among the primary causes of cancer-related morbidity and mortality worldwide. The objective of this study was to evaluate the supportive care needs of survivors of breast cancer and examine how these needs are related to various background factors. To accomplish this, a cross-sectional study was carried out with 116 breast cancer survivors, selected using a convenient sampling method. Data were …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 3, 2024 · pp. 39–42 Read article
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A Study on Feature Subset Selection in Feature Streams of Dynamic Data
Abstract: As the use of real-time data with high dimensions continues to expand across various domains, selecting important features from the dataset is a key step to improve the predictive accuracy and time taken to build a machine learning model. In datasets where not all features are available at the same time and we are unaware of the total number of features, and features arrive at different time stamps, for example, …
Published in Current Trends in Signal Processing · Vol. 15, Issue 3, 2025 · pp. 26–32 Read article