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10 articles for “Pneumonia detection”
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Pneumonia Detection and Classification Using Deep Learning
Abstract: Pneumonia, an infectious lung disease primarily caused by bacteria, often exacerbated by environmental factors, leads to the accumulation of pus in the lung’s alveoli. Accurate diagnosis through chest X-rays, ultrasounds, or lung biopsies is crucial to avoid misdiagnosis and ensure proper treatment, crucial for patients’ quality of life. Diagnostic capacities have been greatly improved by deep learning advances, especially with convolutional neural networks (CNNs). This research presents a robust CNN-based …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 9–19 Read article
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Stacked Generalization-Based Deep Learning Approach for Pneumonia Detection
Abstract: The proposed work focuses on a stacked generalization-based approach for diagnosing pneumonia from chest X-ray images. It utilizes regularization, early stopping, and data augmentation to deal with overfitting. It uses safe level SMOTE to deal with class imbalance and attention-based feature fusion to adaptively weigh features based on their importance. It uses two publicly available datasets (RSNA and Kermany) with ground truth provided by expert radiologists. The proposed work used …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 12, Issue 3, 2025 · pp. 20–31 Read article
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Advancements in Pneumonia X-Ray Image Detection: A Review
Abstract: Pneumonia remains a primary cause of morbidness and mortality worldwide, necessitating the continuous advancement of diagnostic techniques for timely and accurate detection. Pneumonia is common, it is potentially a life-threatening infection for respiration, poses significant challenges to healthcare systems worldwide. Recently, the arrival of deep learning techniques has stirred up the field of medical imaging, offering promising avenues for enhanced pneumonia detection. In this paper, the advancements in pneumonia detection …
Published in OmniScience: A Multi-disciplinary Journal · Vol. 15, Issue 1, 2025 · pp. 1–11 Read article
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Detection of Pneumonia in COVID-19 Patients Using X-ray Images
Abstract: This study explores the use of chest X-ray image analysis and deep learning methods to identify pneumonia in COVID-19 patients. Due to the pandemic, Proper as well as immediate examination of COVID-19 is now essential for patient care and disease control. This study proposes a novel approach that uses convolutional neural networks (CNNs) to automatically predict pneumonia in COVID-19 patients using chest X-ray images. In this study, an X-ray of …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 13–23 Read article
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Deep Learning-Based Pneumonia Diagnosis: A Comparative Review of Models and Metrics
Abstract: Pneumonia is a common viral infection that affects a large percentage of people worldwide. It is more common in developing and impoverished areas because of factors like poor sanitation, crowded living quarters, pollution in the environment, and restricted access to medical facilities. In order to improve survival chances and gain access to therapeutic therapies, pneumonia must be diagnosed as soon as possible. A type of artificial intelligence called deep learning …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 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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Unmasking Human Metapneumovirus: The Emerging Threat to Vulnerable Populations
Abstract: Human Metapneumovirus (HMPV) is a contagious respiratory virus that commonly spreads among individuals. It can cause serious infections, especially in high-risk groups like infants, older adults, and individuals with weakened immune systems.It is a major contributor to acute respiratory illnesses. Since its discovery in 2001, HMPV has been identified as a common cause of both upper and lower respiratory tract illnesses, with clinical presentations ranging from mild symptoms to severe …
Published in International Journal of Virus Studies · Vol. 2, Issue 1, 2025 · pp. 16–24 Read article
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An IoT-Based Integrated Vehicle Safety System for Accident Detection and Driver Monitoring
Abstract: Driver fatigue, alcohol and slow response of emergency services are among a significant issue of road accidents. The paper will provide a real-life example of an IoT-based vehicle safety system, which will combine the accident detection, driver drowsiness and alcohol sensors with a cohesive system. The proposed system consists of use of accelerometer for sudden collision detection, infrared eye blink sensor for determining alertness of the driver and MQ-3 alcohol …
Published in International Journal of Electronics Automation · Vol. 4, Issue 2, 2026 Read article
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A Screening Study on Occurrence and Distribution of Urinary Tract Infections Among Suspected Cases (Pyuria, With or Without Symptoms) During Pregnancy
Abstract: Background: Urinary tract infection is one of the most frequently seen medical complications in pregnancy. Methods: Ethical approval was granted for this research. The study employed a time-bound prospective design; total pregnant women (900) were categorized into those suspected of having UTI (pyuria, with or without symptoms) and those not suspected. Asymptomatic bacteriuria is diagnosed through a urine specimen with an appropriate microscopic examination, followed by culture. Results: The occurrence …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 13, Issue 3, 2024 · pp. 13–20 Read article
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Extended-spectrum beta-lactamases (ESBLs) and Metallo-beta-lactamases (MBLs): A Review
Abstract: Gram-negative bacteria produce extended-spectrum beta-lactamases (ESBLs) and metallo-beta-lactamases (MBLs), enzymes that play a crucial role in antibiotic resistance. These enzymes enable the bacteria to withstand a wide array of beta-lactam antibiotics, including penicillins, cephalosporins, and carbapenems. The production of these enzymes, particularly by organisms, such as Escherichia coli and Klebsiella pneumoniae, complicates treatment options for severe infections, leading to increased morbidity and mortality in clinical settings. ESBLs are primarily responsible …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 15, Issue 2, 2025 · pp. 8–19 Read article