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363 articles for “diagnosis”
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Drug-Induced Liver Injury: Hepatotoxicity and Treatment - A Literature Review
Abstract: Drug-induced liver injury (DILI) is a major clinical and regulatory challenge, posing risks to patient safety and drug development worldwide. As the primary organ responsible for xenobiotic metabolism, the liver is particularly susceptible to toxic injury from prescription drugs, over-the-counter medications, herbal products, and dietary supplements. Drug-induced liver injury (DILI) accounts for a substantial proportion of acute liver failure cases and remains a leading cause of post-marketing drug withdrawal. Its …
Published in Research and Reviews: A Journal of Toxicology · Vol. 16, Issue 1, 2026 · pp. 1–17 Read article
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Enhanced Multimodal Disease Prediction Using Hybrid Ensemble Learning and AutoML Techniques
Abstract: The integration of hybrid ensemble learning and automated machine learning (AutoML) is revolutionizing disease prediction by addressing the complexity, imbalance, and high dimensionality inherent in medical datasets. This paper proposes an advanced pipeline that combines diverse ensemble learning models with AutoML-based optimization to predict chronic diseases such as kidney diseas-e, Parkinson’s disease, and lung cancer. Publicly available datasets from UCI and PhysioNet repositories were preprocessed using outlier removal, normalization, and …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Effectiveness of Public Health Campaigns in Reducing Oral Cancer Incidence in Urban Maharashtra
Abstract: Introduction: Oral cancer is a major public health problem in urban Maharashtra which can be attributed to high consumption of tobacco, late presentation, and poor awareness. To tackle these issues, public health campaigns have been established to encourage early diagnosis, lifestyle modification, and availability of health resources. This study assesses the impact of these campaigns on the reduction of oral cancer incidence and awareness level in the population. Methods: This …
Published in International Journal of Evidence Based Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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Retained Placenta in Dairy Cows: Causes, Consequences and Effective Strategies for Sustainable Dairy Development
Abstract: Retained placenta (RP) is a common reproductive disorder in dairy cows that poses a significant threat to reproductive efficiency, milk yield, and overall herd productivity. The condition, characterized by the failure to expel fetal membranes within 24 hours post-calving, results from a complex interplay of metabolic, endocrine, nutritional, and management-related factors. Key causative agents include dystocia, twin births, premature calving, mineral imbalances, oxidative stress, immune suppression, and hormonal disruptions, particularly …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 Read article
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A Qualitative Study on the Lived Experiences of Women with Polycystic Ovary Syndrome Attending Gynecology OPD, Bangalore
Abstract: Polycystic ovary syndrome (PCOS) is a prevalent hormonal disorder among women of reproductive age, affecting multiple aspects of their well-being, including physical, psychological, emotional, social, and spiritual dimensions. Despite its widespread occurrence, the lived experiences of women with PCOS remain inadequately understood. The present qualitative study aimed to explore and interpret these lived experiences to enhance professional awareness, improve understanding, and promote better support for affected women. A phenomenological research …
Published in International Journal of Midwifery Nursing And Practices · Vol. 3, Issue 2, 2025 · pp. 30–40 Read article
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Optical Fibre Pressure Sensor in Medicine: A Study
Abstract: In the intricate landscape of human health, precise measurement of physiological parameters is paramount for accurate diagnosis, effective treatment, and continuous patient monitoring. Among these vital parameters, pressure plays a critical role – from the subtle pulsatile rhythm of blood flow to the immense force of an intracranial hemorrhage. For decades, traditional electronic pressure sensors have served this purpose, yet they often come with inherent limitations: concerns about electrical interference, …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 3, 2025 · pp. 18–27 Read article
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Implementation and Impact of Lean Manufacturing: A Critical Review and Framework for Adoption
Abstract: Lean manufacturing has become a vital approach for organizations seeking to enhance efficiency, reduce waste, and strengthen competitiveness in dynamic industrial environments. Although lean principles are well established, industries continue to experience inconsistencies in implementation outcomes due to differences in organizational readiness, employee involvement, and managerial commitment. This study critically reviews existing research on lean manufacturing to examine its practical impact, the factors influencing its success, and the challenges that …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 1–7 Read article
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A Study of Optical Sensor in Clinical applications
Abstract: The escalating demand for precise, real-time, and minimally invasive diagnostic and monitoring tools in clinical practice has propelled the development of sophisticated sensor technologies. Among these, optical sensors have emerged as a cornerstone, leveraging the interaction of light with biological matter to translate molecular or cellular events into quantifiable signals. Their inherent advantages – including high sensitivity, specificity, rapid response times, non-ionizing nature, and potential for miniaturization – make them …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 1–7 Read article
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A Study on Optical Stethoscope
Abstract: The traditional stethoscope, a staple in medical diagnosis, has remained relatively unchanged since its inception. However, with the advent of cutting-edge technologies, a revolutionary Optical Stethoscope design has emerged, poised to transform the field of medicine. In a breakthrough that promises to transform the medical landscape, a team of innovative engineers and researchers has unveiled the results of their pioneering work on optical stethoscope design. This revolutionary device is set …
Published in International Journal of Optical Innovations & Research · Vol. 3, Issue 2, 2025 · pp. 22–28 Read article
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Knowledge, Awareness, and Perceptions of Cervical Cancer and Screening Among Women in Rural South India
Abstract: Background: Cervical cancer is still a major public health problem in South India, with rising figures of morbidity and mortality, in spite of progress in prevention, early detection, and treatment. Cervical cancer is the second leading cause of death due to cancer among Indian women, with around 123000 new cases and 67000 deaths every year. The delay in diagnosing CVD and low participation in screening programs is due to poor …
Published in International Journal of Oncological Nursing and Practices · Vol. 3, Issue 2, 2025 · pp. 1–8 Read article
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A Review of Literature on Breast Cancer: Molecular Insights, Clinical Approaches, and Future Perspectives
Abstract: Breast cancer is the leading cause of morbidity and mortality in women globally. Although both men and women can get the condition, women are more likely to get it, and its prevalence has been rising globally in recent years. The epidemiology, risk factors, pathophysiology, diagnosis, treatment options, and survival rates of breast cancer are all examined in this review of recent research. Breast cancer can show up as a lump …
Published in International Journal of Oncological Nursing and Practices · Vol. 3, Issue 2, 2025 · pp. 15–20 Read article
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The Impact of Nanotechnology in Transforming Neuro-oncology - A Comprehensive Review
Abstract: The treatment of central nervous system (CNS) tumours, including aggressive malignancies like glioblastoma, faces significant challenges. The blood–brain barrier (BBB) blocks nearly 98% of small-molecule drugs from achieving therapeutic levels in the brain, and the heterogeneity of these tumours frequently contributes to treatment resistance and poor outcomes. Traditional approaches, including chemotherapy and radiotherapy, are hindered by systemic toxicity and inadequate drug penetration. Nanotechnology provides a promising alternative, as nanoparticles (NPs) …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 · pp. 627–637 Read article
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Cancer Chemotherapy-Induced Cachexia: Bridging Mechanisms, Management, and Future Therapies
Abstract: Involuntary weight loss, skeletal muscle atrophy, adipose tissue depletion, anorexia, and systemic inflammation are all symptoms of chemotherapy-induced cachexia, a complex illness. Although it is common, it remains poorly understood and is often referred to as an "orphan disease." This study covers the epidemiology, pathophysiology, clinical symptoms, diagnosis, treatment, and emerging treatment options for chemotherapy-induced cachexia. To comprehend the causes, clinical results, and therapeutic approaches, a literature-based synthesis of recent …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 17–26 Read article
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Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Method: A Comprehensive Review
Abstract: Structural health monitoring (SHM) has a critical role in ensuring civil infrastructure safety, reliability, and durability through real-time, condition-based monitoring. Traditional SHM systems employ hundreds of sensors such as accelerometers, strain gauges, and displacement transducers for monitoring vast amounts of data for structural inspection, but do not effectively manage complicated nonlinear data. This research paper, “Optimization of Structural Health Monitoring Using Artificial Neural Network and Comparison with Traditional Methods,” investigates …
Published in Journal of Structural Engineering and Management · Vol. 13, Issue 1, 2026 · pp. 23–33 Read article
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A Comprehensive Review on Federated Learning in Disease Detection
Abstract: Healthcare data, which is frequently dispersed among various organisations, has enormous potential to improve predictive analytics and illness identification. However, there are substantial privacy & legal obstacles to sharing this private data for centralised model training. Federated Learning is a paradigm shift that allows several organisations to work together to build a global model without disclosing raw patient information. Federated Learning uses a larger dataset to provide more reliable insights …
Published in Emerging Trends in Personalized Medicines · Vol. 3, Issue 1, 2026 · pp. 1–21 Read article
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Log Identification and Monitoring System Using Generative AI
Abstract: In contemporary software ecosystems, application and infrastructure logs play a vital role in ensuring system reliability, performance optimization, fault diagnosis, and security compliance. As applications become increasingly distributed and cloud native, the volume, velocity, and variety of generated log data have grown dramatically. This rapid expansion makes traditional manual log inspection inefficient, error-prone, and largely impractical. To address these challenges, this paper proposes an artificial intelligence (AI) driven log monitoring …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 08–16 Read article
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Comparative Analysis of Supervised Learning Algorithms
Abstract: Supervised learning is a fundamental and widely used branch of machine learning in which models are trained on labeled datasets, meaning that each input is associated with a known output. Supervised learning algorithms develop predictive capability by understanding the mapping between input variables and corresponding output labels, enabling them to accurately forecast outcomes for previously unseen data. Due to this capability, supervised learning has found extensive applications across diverse domains …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 · pp. 25–30 Read article
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Skin Disease prediction and classification from dermoscopy images using Neural Network
Abstract: Skin diseases are among the most common health-related problems affecting people of all age groups, and their occurrence often varies with seasonal and environmental conditions. Delayed or incorrect diagnosis of skin disorders can lead to severe complications, making early and accurate detection extremely important for effective treatment and prevention. In recent years, rapid advancements in deep learning and neural network technologies have significantly contributed to the development of automated medical …
Published in Journal of Computer Technology & Applications · Vol. 17, Issue 1, 2026 Read article
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Advanced Polymer Nanocomposite EEG Electrodes for Enhanced Epileptic Seizure Detection: A Comparative Analysis
Abstract: Electroencephalography (EEG) has been very important in the detection of epileptic seizures so as to enable successful diagnosis, surveillance and therapy of epilepsy. Nevertheless, EEG electrodes based on traditional metals may be limited due to high or high contact impedance, lack of biocompatibility, discomfort to patients and prone to motion artifacts, which interfere with signal quality and diagnostic adequacy. The recent progress in material science has resulted in coming up …
Published in Journal of Polymer & Composites · Vol. 14, Issue 1, 2026 Read article
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A Dual-Model Deep Learning Framework for Early Alzheimer’s Detection Using Clinical Data and Neuroimaging with Architectural Performance Analysis
Abstract: Alzheimer’s disease (AD) poses a significant global health challenge due to its increasing prevalence and the absence of definitive cures. Early diagnosis is crucial for effective intervention and management. This study presents a dual-model deep learning framework for the early detection and classification of AD using both structured clinical data and neuroimaging datasets. Model 1 utilizes a greedy layer-wise autoencoder approach applied to structured data, achieving optimal binary classification accuracy …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 1–12 Read article