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363 articles for “diagnosis”
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A Review on AI and Machine Learning for Predictive Maintenance and FDD in RAC Systems
Abstract: The paper reviews the existing AI/ML methods first in the general context of predictive maintenance and FDD of RAC systems, then specifically focusing on granular cooling appliances. Perspectives and insights are provided on the reasons why potentially valuable models do not make it into practice more often, and where future research and development should be headed. New emerging topics for decision support systems to include domain knowledge and physics-based modeling …
Published in Journal of Refrigeration, Air conditioning, Heating and ventilation · Vol. 13, Issue 1, 2026 · pp. 15–25 Read article
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Synthesis, characterizations, and challenges of magnetic Zn x Fe 2-x O 3 nanoparticles
Abstract: Diluted magnetic semiconductors comprising magnetic nanoparticles are a driving force in a variety of applications, including biomedicine, bioelectronics, photocatalytic activities, and nanosensors. However, the functionality of these nanomaterials can be influenced by several factors, such as synthesis route, characterization procedures, source, crystal size, and morphology. In this research, emphasis is devoted to synthesizing and characterizing magnetic nanoparticles. Most importantly, it is focused on biological methods, Co-precipitation methods, hydrothermal Gravity methods, …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 2, 2025 Read article
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Description & Prevention of Omicron
Abstract: November 9, 2021, Botswana becomes the first country to recognise it (Nov 11 2021). The new variant (B.1.529) has been represented in 77 countries. Omicron presents 32 changes in spike protein Scribd, restricting the point of interaction with the ACE2 receptor protein. Computational shows and components’ recreation has been applied to investigate the collaboration between the SARS-CoV-2 RBD and the ACE2 receptor. The receptor-binding domain (RBD), which more barely joins …
Published in Research & Reviews: A Journal of Pharmacognosy Read article
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Uterine Leiomyosarcoma: A Diagnostic Dilemma
Abstract: Tumours that fall under the category of uterine malignancies include carcinosarcomas, leiomyosarcomas, endometrial stromal sarcomas, and undifferentiated sarcomas. Of them, leiomyosarcoma is the most common subtype, while still quite uncommon—it accounts for 1% to 2% of uterine cancers. Since postmenopausal bleeding is typically present in leiomyosarcomas, prompt detection is essential for successful treatment. This case study features a 50-year-old female patient who had postmenopausal bleeding, which is a common sign …
Published in International Journal of Pathogens · Vol. 1, Issue 1, 2024 · pp. 38–42 Read article
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Comparative Analysis of Data Augmentation Techniques in CNN-based Classification of Atelectasis
Abstract: This research delves into the critical issue of atelectasis, its causes, and potential complications if left untreated. Leveraging deep learning algorithms, particularly convolutional neural networks (CNN), the paper explores their application in medical image analysis, focusing on the detection of atelectasis using the “chestX-ray8” database. The study compares various data augmentation techniques for improved accuracy, showcasing the importance of augmentation in enhancing model generalization. Through meticulous experimentation and evaluation, the …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 3, 2024 · pp. 1–8 Read article
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Alzheimer’s Disease Detection Using ML Algorithm
Abstract: A degenerative neurological state of affairs, Alzheimer's disease (AD) gradually impairs cognitive and functional capacities, especially in people over 65. Early AD detection is crucial for efficient management and treatment prep. This study delves into novel approaches for the early detection of AD using non-invasive methods. We've implemented a blend of neuroimaging data analysis and machine learning algorithms to pinpoint markers indicative of the disease during its initial phases. Our …
Published in Journal of Experimental & Applied Mechanics · Vol. 15, Issue 3, 2024 · pp. 53–57 Read article
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Towards smart cancer care - AI enhanced monitoring and intervention
Abstract: According to estimates from the World Health Organization (WHO) for 2022, cancer is one of the leading causes of mortality, accounting for roughly 16% of all deaths globally. The goal of the cancer community is to improve the lives of those who are impacted by cancer and to cut the cancer death rate in half during the next several years. If cancer is identified early and treated, its impact on …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 1, 2025 · pp. 38–44 Read article
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Ethical Consideration in the Use of Artificial Intelligence in Medicine and Healthcare
Abstract: Artificial Intelligence (AI) in medicine and healthcare offers tremendous potential for improving patient care, increasing the precision of diagnoses, and increasing operational efficiency. To ensure responsible application, however, the swift uptake of AI technologies also brings up important ethical concerns that need to be addressed. This article explores various ethical challenges in healthcare AI, including concerns about algorithmic bias, data privacy, informed consent, and accountability. Patients must be aware of …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 1, 2025 · pp. 23–28 Read article
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Radiopharmaceuticals use as a nuclear medicine for a Treatment of Disease
Abstract: Radiopharmaceuticals are radioactive substances that contain a bonded radionuclide with the intention of directing the radionuclide to a specific place for treatment or imaging. Radiopharmaceuticals are employed in nuclear medicine for cancer therapy as well as other therapeutic and diagnostic applications. Therefore, the primary goal of this study is to identify the key metal complexes and radioactive elements utilized in radiopharmaceutical applications. The sodium and methylenediphosphonate (MDP-99mTc) complexes, along with …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 17–21 Read article
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Numerical Study of Natural Convection Heat Transfer in Porous Particles Through Composite Filters
Abstract: The study of heat transmission through porous materials within the confines of reactor configurations stands as a pivotal realm of inquiry in the realms of engineering and the applied sciences, possessing wide-ranging applications spanning from soil mechanics to the refinement of heat exchange systems. Porous substances, distinguished by their interconnected voids or interstices, present an array of reactor forms that profoundly shape the flow of fluids and the conveyance of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 268–279 Read article
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A Comparative Study of Deep Learning Methods for Depression Detection in Social Media Data
Abstract: With the rise of social media platforms like Twitter, Reddit, and Facebook, individuals increasingly share personal information about their moods, behaviors, and mental states. This trend provides a unique opportunity to leverage large-scale textual data for understanding and monitoring mental health conditions, particularly depression, a prevalent and challenging mental health issue. Traditional depression assessments are often confined to clinical environments and lack the capacity for real-time monitoring. In contrast, social …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 3, 2025 · pp. 55–65 Read article
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Feature Extraction and Analysis of Bearing Faults: A Review
Abstract: One of the most important steps in identifying bearing problems is feature extraction. In order to provide a more meaningful dataset, it entails locating and extracting pertinent features from raw bearing vibration signals. Tasks involving categorization and prediction can then make use of these attributes. In many practical applications, such as monitoring rotating machinery or electronic components, the raw signals collected (e.g., vibration, current, temperature) are often complex, high-dimensional, and …
Published in Trends in Mechanical Engineering & Technology · Vol. 15, Issue 2, 2025 · pp. 20–28 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article
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Deep Learning-Based Alzheimer’s Disease Detection: A CNN Approach
Abstract: Alzheimer’s disease (AD) is a neurological condition that worsens with time and impairs a patient’s quality of life by causing cognitive loss. For prompt intervention and management of AD, early identification is essential. In this work, we propose a deep learning-based method for automatically classifying Alzheimer’s disease from medical imaging data using convolutional neural networks (CNNs). Our algorithm is intended to evaluate brain MRI images and detect anatomical variations suggestive …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 15, Issue 3, 2025 Read article
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AI in Mental Health: New Developments and Prospects
Abstract: Artificial intelligence (AI) has revolutionised numerous industries, including the mental health care sector.In order to clarify present trends, ethical issues, and future prospects in this ever-evolving subject, this paper examines the integration of AI into mental healthcare. Recent research, AI application examples, and ethical issues influencing the area were all included in this study. Research and development trends and regulatory frameworks were also examined.With applications including the early detection of …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 3, 2025 Read article
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Shadows of Uncertainty: When Pneumonia Isn’t Pneumonia
Abstract: Pneumonia is a common medical condition encountered in hospitalized patients and remains a cause of morbidity worldwide. Identifying and initiating appropriate treatment in febrile patients who present with respiratory symptoms and radiographic infiltrates, reduce hospital stay, minimize complications, and lower healthcare costs. However, the assumption that every pulmonary infiltrate or opacity seen on a radiological imaging represents an infectious process such as pneumonia can lead to misdiagnosis, unnecessary investigations, prolonged …
Published in International Journal of Pathogens · Vol. 3, Issue 1, 2026 · pp. 24–29 Read article
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IOT and algorithmic intelligent motor health monitoring as well as maintenance prediction
Abstract: Manufacturing, transportation, and energy systems rely largely on industrial electric motors, and their untimely failure can result in expensive downtime, safety hazards, and decreased operational efficiency. The majority of traditional motor maintenance procedures rely on reactive methods or routine inspections, which frequently miss early-stage problems and lead to needless maintenance or unexpected breakdowns. This project offers an Intelligent Motor Health Monitoring and Predictive Maintenance System that combines Internet of Things …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 28–37 Read article
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Role of Artificial Intelligence in Simulation and Therapeutics in Neurodegenerative Diseases
Abstract: Neurodegenerative diseases, such as Alzheimer’s disease, Parkinson’s disease, Huntington’s disease, etc., are a cause of significant mortality rates due to a lack of curative treatments and their complex nature. Traditional therapeutic methodologies have several disadvantages such as slow diagnosis and a lack of effective treatments. They mainly focused on the management of the disease rather than curing it. The integration of artificial intelligence in the simulation and therapeutics of neurodegenerative …
Published in Research and Reviews: A Journal of Neuroscience · Vol. 16, Issue 1, 2026 · pp. 19–29 Read article
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A Case Report of Advanced Periampullary Carcinoma: Palliative Chemotherapy Following Whipple’s Surgery
Abstract: This case report delves into the complex management of a 60-year-old female patient diagnosed with Stage 4 periampullary carcinoma, encompassing the pancreatic head. Presenting with difficulty in eating, diagnostic investigations, including ERCP, confirmed the diagnosis, leading to Whipple's surgery. Postoperatively, liver metastasis was identified, prompting palliative intervention through stenting and the initiation of a GEMOX chemotherapy regimen. The patient responded favorably to the initial chemotherapy cycle, leading to a planned …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 13, Issue 1, 2024 · pp. 1–6 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