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122 articles for “Clinical data analysis”
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Clinical Profiles of Patients Presenting with Hypoglycemia in Emergency Department of Bir Hospital
Abstract: Hypoglycemia stands as a primary reason for visits to the Emergency Department (ED), ranking high among the most frequent and easily avoidable hormonal emergencies. The aim of this research is to investigate the occurrence of hypoglycemia and identify its underlying causes. As the number of diabetes cases rises, along with different methods of tightly managing blood sugar levels, the likelihood of hypoglycemia also increases. Given that extended periods of hypoglycemia …
Published in Research and Reviews: A Journal of Health Professions · Vol. 14, Issue 3, 2024 · pp. 19–39 Read article
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A Cross-sectional Study to Analyse Level of Stress among Nursing Students of Christ College of Nursing, Jagdalpur, Chhattisgarh
Abstract: Nursing education combines rigorous academic training with demanding clinical responsibilities, exposing students to multiple stressors that may affect their psychological well-being, academic performance, and professional growth. Assessing stress levels and their association with socio-demographic variables is essential for developing effective support strategies. This study aimed to assess the level of stress among nursing students and determine its association with selected socio-demographic characteristics. A descriptive cross-sectional study was conducted among 150 …
Published in Journal of Nursing Science & Practice · Vol. 16, Issue 1, 2026 · pp. 1–10 Read article
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Embarking on the Frontier: A Comprehensive Study of various traditional Technologies and creating awareness about latest technologies for Breast Cancer Screening amongst various Hospitals in India
Abstract: This extensive study explores the landscape of conventional technologies used in Indian hospitals for Breast Cancer Screening. The study comprehensively examines commonly used techniques, including Mammography, Ultrasound and Clinical Breast Examination in order to provide a holistic understanding of existing screening methods. The study also investigates how well-informed medical facilities are on the newest technology in breast cancer screening, including AI based methods.The acceptance rates and challenges involved with introducing …
Published in Emerging Trends in Chemical Engineering · Vol. 11, Issue 1, 2024 · pp. 80–86 Read article
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The Role of Artificial Intelligence in Mental Health: Applications in Neurodegenerative Disorders
Abstract: Artificial intelligence (AI) has significantly changed many aspects of medical care, particularly the early evaluation, therapy, and management of neurodegenerative illnesses like Alzheimer's, disease, Parkinson's diseases, and Huntington's diseases. The current research explores the application of AI in mental health with respect to neurological disorders, especially advancements in cognitive examination, neuroimaging analysis, predictive modeling, and customized therapy modalities. Artificial intelligence (AI) systems have shown enormous potential in detecting minute biomarkers …
Published in Research and Reviews : A Journal of Biotechnology · Vol. 15, Issue 3, 2025 · pp. 34–40 Read article
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Advancements in AI-Driven Diagnostics for Dental Health: A Comprehensive Review
Abstract: Dental diseases, also known as oral diseases or dental conditions, encompass a range of health problems affecting the teeth, gums, mouth, and associated structures. These conditions can lead to pain, discomfort, and severe complications if left untreated. Early detection and accurate diagnosis are crucial for effective treatment and prevention of further complications. This comprehensive literature review aims to identify common dental problems such as Tooth Decay (Cavities), Gingivitis, Periodontitis, and …
Published in Current Trends in Signal Processing · Vol. 14, Issue 2, 2024 · pp. 1–7 Read article
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Depression Detection Using Machine Learning: A Comprehensive Review
Abstract: Depression remains one of the most prevalent mental health conditions globally, yet it frequently goes undiagnosed due to the reliance on subjective evaluation methods. With the growing availability of digital behavioral data and significant progress in machine learning (ML), new possibilities have emerged for the automated detection of depression. This review offers a detailed examination of recent advancements in ML-driven approaches to identifying depressive symptoms. It covers a range of …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 27–32 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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FutureGen – Predicting Genetic Health
Abstract: FutureGen is an intelligent web-based system developed to help couples assess the risk of genetic disorders in their future child through data-driven analysis. The system brings together modern web technologies and machine learning to offer accurate and accessible predictions. The frontend, built with React, provides an intuitive interface for user interaction, while a Flask-based backend API handles model inference and manages communication with the Supabase database, which securely stores user …
Published in International Journal of Genetic Modifications and Recombinations · Vol. 4, Issue 1, 2026 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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Muscle vs. Heart: A Comprehensive Review of Anabolic Steroid-Induced Cardiovascular Risks
Abstract: Anabolic-androgenic steroids (AAS) are widely used by athletes and bodybuilders to enhance muscle mass and performance. However, their misuse is associated with serious and often underrecognized cardiovascular risks. Despite their popularity, particularly among young adults, the long-term consequences of AAS abuse on cardiovascular health remain insufficiently explored in the literature. This review aims to: 1. Analyze the cardiovascular implications of AAS use. 2. Elucidate the molecular and physiological mechanisms contributing …
Published in International Journal of Toxins and Toxics · Vol. 3, Issue 2, 2026 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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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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Biomarkers in Cancer Research: Discovery and Future Directions
Abstract: Biomarkers have transformed the study of cancer, providing critical information regarding prognosis and therapy response and promoting earlier diagnosis. This paper discusses the different parts of cancer biomarkers, starting with their description, classification, and major types, which are the groundwork for understanding their clinical role. The discussion on the development and validation process of biomarkers is then undertaken, focusing on state-of-the-art techniques and the importance of ensuring accuracy and reproducibility. …
Published in Trends in Drug Delivery · Vol. 12, Issue 1, 2025 · pp. 22–26 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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Patterns and Variations in Complementary Feeding Practices Among Mothers of Children Aged 6–24 Months Attending Immunization Clinics in Mandi Gobindgarh, Punjab, India
Abstract: Introduction: Complementary feeding introduces solid or semisolid foods to an infant’s diet while breastfeeding. In India, feeding infants and young children is determined by their socioeconomic status, cultural practices, and healthcare access. The study assesses the feeding practices of mothers with children aged 6–24 months who come for immunization at Mandi Gobindgarh, Punjab. Methods: A cross-sectional study was conducted with 350 mothers selected through systematic random sampling. A structured questionnaire …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 15, Issue 3, 2025 · pp. 43–53 Read article
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Dr. Somenath Dutta, Discoverer of Micro-RNA (MiRNA) Therapeutic to Prevent Harmful Zika Virus for Liver Cancer: A Scientometric Portrait
Abstract: Dr. Somenath Dutta allies Rahul is a global recognized scientist for his outstanding recent discovery of “miRNA therapeutics for the Zika virus” at the age of 26 years, which can be cured Liver Cancer and allied health problems due to Zika virus disease. This study covers his 12 publications in variety of forms including 07 journal articles (59%), 03 conference papers (25%), 01 dissertation, and 01-chapter paper during 2019-2024. All …
Published in International Journal of Virus Studies · Vol. 2, Issue 2, 2025 · pp. 22–36 Read article
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Red Cell Distribution in Pregnancy Associated with Preeclampsia Patients in Worldwide: A Brief Review
Abstract: Introduction: Preeclampsia (PE) is a major obstetric problem contributing considerably to maternal and prenatal morbidity and mortality worldwide. Preeclampsia varies in incidence in India from 5% to 15%. The role of this hematological parameter in clinical assessment, differential diagnosis, and prognosis evaluation of PE remains unclear. Thus, the purpose of the current review was to investigate the red cell distribution width (RDW) in preeclampsia, analyze its importance for early diagnosis, …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 14, Issue 1, 2024 · pp. 6–12 Read article
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A study on IoT and AI for Predictive Modeling and Control of Infectious Disease Transmission
Abstract: Background: The global response to novel and recurring infectious diseases is frequently hindered by surveillance systems that are slow, siloed, and reactive. Traditional epidemiology relies on retrospective analysis of clinical reports, often missing the critical early phase of autocatalytic spread. The urgency of modern public health necessitates a shift toward real-time, predictive intelligence. Methods: This study investigates the development and deployment of a synergistic paradigm integrating the Internet of Things …
Published in International Journal of Pathogens · Vol. 2, Issue 2, 2025 Read article
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Transfer Learning in Deep Learning Models for Medical Imaging: Utilizing Pretrained Models to Improve Performance in Medical Image Analysis
Abstract: Transfer learning is now a trending technique in deep learning, especially in medical imaging. This technique solves landmark problems by utilizing the pre-trained models, including the limited availability of the annotated medical data and the time-consuming computational costs of training deep learning models from scratch. The generalizability of deep models could increase diagnostic precision for specific medical tasks, require fewer samples to train, and take less time to train due …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 1, 2025 · pp. 67–85 Read article
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A Study on the Knowledge of Arterial Blood Gas (ABG) Analysis Among Staff Nurses in a Rural Hospital Setting
Abstract: To evaluate the comprehension of Arterial Blood Gas (ABG) analysis among staff nurses in a designated Rural Hospital, this study aimed to assess their knowledge level and correlate it with specific demographic variables. Utilizing a descriptive approach, the study encompassed all staff nurses within the Rural Hospital, with a sample of 50 individuals meeting the inclusion criteria: completion of either a Diploma in Nursing and Midwifery (GNM) or a Degree …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 2, 2024 · pp. 1–21 Read article