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357 articles for “ear diseases”
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Hemoglobin Electrophoresis to Identify Adult Hemoglobin and Abnormal Hemoglobin Bands
Abstract: According to National Thalassemia Welfare Society (NTWS) report, every year, around 3 to 4 lakhs babies are born with one or other form of hemoglobinopathies and around 7% of the world population is carrier of hemoglobinopathies. In India, hemoglobinopathies like thalassemia and sickle cell anemia, are one of the most common hereditary disorders and cause a major health problem. In India, incidence of sickle cell and β thalassemia differ from …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 12, Issue 2, 2023 · pp. 1–6 Read article
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Retinal Disease Detection Using Deep CNN
Abstract: Age-related macular degeneration, glaucoma, and diabetic retinopathy are the three main causes of blindness in the globe. To avoid visual loss, early identification and treatment of these disorders are essential. The goal of this research is to create an automated method for detecting retinal diseases by analyzing retinal fundus pictures with machine learning techniques. Python and the Tkinter package for the graphical user interface are used in the construction of …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 2, 2024 · pp. 46–50 Read article
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Generating Weights for Fuzzy Decision Making Mechanism to Diagnose Heart Disease
Abstract: AbstractHeart disease is one of the diseases spread around the world. It suddenly kills the human community. So use of fuzzy logic to diagnosis the heart disease is essential. So the study was conducted with the following components. They are fuzzification, fuzzy decision making mechanism and defuzzification. The crisp values are changed into fuzzy values by fuzzification. Fuzzy decision making mechanism is based on adaptive neuro fuzzy inference system which …
Published in Journal of Computer Technology & Applications · Vol. 6, Issue 2, 2015 · pp. 7–13 Read article
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Cutting-edge Deep Learning Methods for Predicting and Detecting Cardiovascular Diseases
Abstract: Cardiovascular diseases (CVDs) remain a major global health issue, highlighting the need for improved early detection and risk assessment methods. This research investigates the efficacy of both deep learning and traditional machine learning methods in forecasting cardiovascular diseases (CVDs). We evaluate a variety of models, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Multilayer Perceptrons (MLPs), Long Short-Term Memory (LSTM) networks, as well as Logistic Regression (LR), Decision Trees …
Published in Recent Trends in Parallel Computing · Vol. 11, Issue 2, 2024 · pp. 36–42 Read article
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Harvestify: ML Based Tool for Home Gardening and Farming
Abstract: This study presents a cutting-edge application that will transform home gardening and agriculture practices using machine learning (ML) approaches. The main goal is to provide data-driven insights to home gardeners and farmers, enabling them to implement efficient and sustainable farming practices. Crop disease detection, fertiliser recommendation, and a community section for user engagement comprise the three main elements that make up the system's architecture. The Crop Disease Detection module analyses …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 2, Issue 2, 2024 · pp. 18–28 Read article
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Phase-Specific Nutrient Requirements in Broilers: Implications for Behavior, Gut Health, Performance, Meat Quality, Welfare, and Economics
Abstract: The broiler industry plays an inevitable role in global food security, requiring optimal formulation strategies tailored to each growth phase, starter, grower, and finisher for sustainable production. This review explores phase-specific nutrient requirements and their implications for broiler performance, meat quality, welfare, and economics. During the starter phase (1–10 days), nutrition focuses on immune development, gut health, and skeletal growth, with high protein and low energy needs. In the grower …
Published in Research and Reviews : A Journal of Life Sciences · Vol. 15, Issue 1, 2025 · pp. 5–15 Read article
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Detection and Classification of Alzheimer’s Disease Using Deep Learning Technique
Abstract: It is crucial that people with Alzheimer's disease (AD) receive a proper diagnosis to begin preventative action before irreparable brain damage develops. Most people who suffer from Alzheimer's disease (AD), a neurological condition that progresses, are older than 65. The area of interest (ROI) in the hippocampus has been extensively studied for several purposes, including neurological illness research, stress development monitoring, and memory function analysis. Moreover, a connection between Alzheimer's …
Published in Recent Trends in Sensor Research & Technology · Vol. 12, Issue 1, 2025 · pp. 15–20 Read article
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Progression of Health and Wellness: Artificial Intelligence (AI) and Deep Learning (DL) for Precision Medicines
Abstract: Deep learning and artificial intelligence in the field of precision medicine is revolutionizing healthcare to make personalized therapeutic approaches desirable based on the unique characteristics of the patient. AI technologies improve diagnostic accuracy by analyzing medical data, spotting patterns and anomalies that human experts may miss. AI-driven models are instrumental in precision medicine, where they can predict patient response to therapies to tailor treatment plans, enhancing outcomes and reducing adverse …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 1–5 Read article
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Novel Approach for Automated Diagnosis of Diabetic Retinopathy
Abstract: Automated and early diagnosis of diabetic retinopathy is a crucial need. Diabetic retinopathy (DR) is the major cause of blindness among people. DR is a progressive disease classified according to the presence of various clinical abnormalities. It doesn’t have any visible symptoms till the disease is at late stage. Therefore, it necessary to detect DR at early stage and to ensure proper treatment. For early detection of DR, different automated …
Published in Journal of Electronic Design Technology · Vol. 7, Issue 1, 2016 · pp. 9–13 Read article
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Development of a Nursing Care Protocol for Patients with Stroke in the First 24 Hours of Thrombolysis
Abstract: Even though thrombolysis in acute stroke predicts good outcome, these patients are at risk for developing complications of thrombolysis as well as the disease itself. Strict monitoring and effective interventions initiated early in the first 24 h can enhance the recovery process and minimize functional disability. This methodological study was undertaken to study the current practices of nursing care and to develop a nursing care protocol for the care of …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 5, Issue 3, 2015 · pp. 27–39 Read article
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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
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Early Heart Failure Recognition for Infants Using Machine Learning
Abstract: The care of newborn infants remains a significant responsibility for healthcare professionals, as ensuring infant survival can often be complex and demanding. Conditions such as heart failure and cardiac arrest in infants are life-threatening and require prompt diagnosis and treatment. Detecting cardiac problems at an early stage can greatly enhance survival outcomes and minimize serious complications. In recent years, machine learning (ML) approaches have become valuable tools for predicting cardiovascular …
Published in International Journal of Emergency and Trauma Nursing and Practices · Vol. 4, Issue 1, 2026 · pp. 1–5 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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A review on Design of Gene Therapy and Its Potential for Craniofacial Regeneration
Abstract: One of the most talked-about topics of the 21st century is gene therapy, which holds the promise of treating many diseases. Current gene therapy research explores a wide range of potential treatments, such as enhancing the body’s immune response to tumors, promoting the formation of new blood vessels in the heart to mitigate heart attacks, and preventing HIV replication in AIDS patients. Gene therapy involves the introduction, alteration, or replacement …
Published in Emerging Trends in Personalized Medicines · Vol. 2, Issue 2, 2025 · pp. 6–12 Read article
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Life Expectancy Rate and Health Facilities in Kachchh District
Abstract: After earthquake due to industrialization, population is growing; so many private hospitals have opened for treatment of different diseases. But the rural areas are deprived of health facilities. In rural areas, 55.50% samples of families agreed that they had suffered from one or the other type of addiction. About 75% samples of rural families do not get pure drinking water. About 72% samples of families agree that they live in …
Published in Journal of Production Research & Management · Vol. 2, Issue 1-2-3, 2012 · pp. 66–78 Read article
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APPLICATION OF ARTIFICIAL INTELLIGENCE IN DRUG DISCOVERY
Abstract: The application of artificial intelligence (AI) in medicine, especially through machine learning (ML), is revolutionizing new-age drug discovery research. AI is found as an efficient and powerful tool to narrow the gap between disease detection and developing and identifying potential therapeutic agents for a cure. This review provides a summary of the latest developments in AI and its potential application in drug discovery for untreatable diseases. The review also examines …
Published in Emerging Trends in Chemical Engineering · Vol. 12, Issue 3, 2025 · pp. 22–29 Read article
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A Systematic Review on Coronary Heart Disease: A Transient Ischemic Stroke
Abstract: Coronary Heart Disease (CHD) and Transient Ischemic Attack (TIA) are significant cardiovascular and cerebrovascular disorders that often share similar risk factors and underlying pathophysiological processes. CHD involves the narrowing or obstruction of the coronary arteries due to atherosclerosis, resulting in diminished blood flow to the heart. A transient ischemic attack (TIA), often called a "mini stroke," occurs when blood flow to the brain is briefly disrupted, usually due to a …
Published in Research and Reviews : Journal of Surgery · Vol. 14, Issue 3, 2025 Read article
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Comparison of K-nearest Neighbor and Artificial Neural Network Classifiers for the Detection of Breast Cancer
Abstract: Breast cancer is the most common type of cancer seen in women in the present day, which is also considered a life-threatening disease. If this cancer can be detected in its early stage it can be a lifesaver for many people around the world. Machine Learning techniques have become one of the hotspots for predicting the early diagnosis of breast cancer. This research work experiments with the two most popularly …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 1, 2024 · pp. 78–83 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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Comprehensive Study and Triggering Factors of Alcoholic and Non-Alcoholic Fatty Liver
Abstract: Over the past few years, fatty liver disease has turned out to be a rather widespread phenomenon and has become a serious issue with the global population nowadays. It comprises alcoholic fatty liver disease and non-alcoholic fatty liver disease, which develop under the influence of various initiating factors, though frequently follow similar pathologies. The overloading of lipids in the hepatocytes in most cases will be the first sign of the …
Published in Research and Reviews: A Journal of Pharmacology · Vol. 16, Issue 1, 2026 · pp. 43–52 Read article