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A Review of Snake Models in Medical MR Image Segmentation
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Developing an efficient algorithm for automated Magnetic Resonance Imaging (MRI) segmentation to characterize tumor abnormalities in an accurate and reproducible manner is ever demanding. This paper presents an overview of the recent development and challenges of the energy minimizing active contour segmentation model called snake for the MRI. This model is successfully used in contour detection for object recognition, computer vision and graphics as well as biomedical image processing including X-ray, MRI and Ultrasound images. Snakes being deformable well-defined curves in the image domain can move under the influence of internal forces and external forces are subsequently derived from the image data. We underscore a critical appraisal of the current status of semi-automated and automated methods for the segmentation of MR images with important issues and terminologies. Advantages and disadvantages of various segmentation methods with salient features and their relevancies are also cited.

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Publication Date
Mon Jan 01 2024
Journal Name
Ieee Access
Patient Monitoring System Based on Internet of Things: A Review and Related Challenges With Open Research Issues
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Publication Date
Tue Jun 15 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Genetic Structure, Transmission, Clinical Characteristics, Diagnosis, Treatment and Prevention of Coronavirus Disease 2019 (COVID-19): A Review
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The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a pandemic of coronavirus disease 2019 (COVID-19) which represents a global public health crisis. Based on recent published studies, this review discusses current evidence related to the transmission, clinical characteristics, diagnosis, management and prevention of COVID-19. It is hoped that this review article will provide a benefit for the public to well understand and deal with this new virus, and give a reference for future researches.

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Publication Date
Wed Mar 04 2026
Journal Name
Journal Of Molecular Pathology
From Dysbiosis to Tissue Destruction: Periodontal Pathogens as Inducers of Gingival Epithelial–Mesenchymal Transition (A Narrative Review)
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Periodontitis is a dysbiosis-driven inflammatory disease in which a pathogenic subgingival biofilm disrupts the host–microbe equilibrium and promotes progressive loss of tooth-supporting tissues. While periodontal destruction has traditionally been explained mainly through the host immune response, increasing experimental and clinical evidence suggests that epithelial–mesenchymal transition (EMT)-like changes in the gingival epithelium may contribute to barrier failure and tissue remodeling during disease progression. EMT is characterized by reduced epithelial adhesion and polarity, alongside a shift toward a mesenchymal-like phenotype with enhanced motility and impaired epithelial barrier function. This narrative review focuses

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Publication Date
Mon Jul 08 2024
Journal Name
Journal Of Microbiology, Biotechnology And Food Sciences
SYNERGISTIC EFFECTS OF NEEM OIL AND GENTAMICIN ON PSEUDOMONAS AERUGINOSA VIA PHZM GENE DOWNREGULATION: A COMPREHENSIVE REVIEW
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Exploring the antibacterial potential of neem oil (Azadirachta indica) in combination with gentamicin (GEN) against pathogenic molds, especially Pseudomonas aeruginosa, has drawn concern due to the quest for natural treatment options against incurable diseases. Prospective research directions include looking for natural cures for many of the currently incurable diseases available now. microbial identification system, were used to identify the isolates. The research utilized a range of methods, such as the diffusion agar well (AWD) assays, TEM (transmission electron microscopy) analysis, minimum inhibitory concentration (MIC) assays, and real-time PCR (RT-qPCR) to analyze bacterial expression and the antibacterial action of neem oil (Azadira

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Publication Date
Wed Jan 01 2025
Journal Name
International Journal Of Hydrogen Energy
A comprehensive review of battery thermal management systems for electric vehicles: Enhancing performance, sustainability, and future trends
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Publication Date
Thu Jan 01 2026
Journal Name
Journal Of Water Management Modeling
Identifying Factors Affecting the Morphological Changes of River Estuaries and Techniques for Analysis and Control: A Review
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Erosion and deposition are natural phenomena in many estuaries that can cause morphological changes, leading to navigation and offshore structure problems. Many previous studies have focused on investigating the morphological changes of estuaries depending on different parameters and their combined effects with erosion and deposition processes, such as maximum flow amplitude, waves, currents, tidal flow, storms, rising sea elevation, maximum turbidity, salinity, and bed roughness height as input parameters. These studies are based on field measurements and numerical simulations by using topographic surveys, soil samples, satellite images, geological data, and bathymetric maps with the aid of ArcGIS. Some of these studies examine the

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
Strengthening or rehabilitation of reinforced concrete (RC) beams using carbon fiber reinforced polymer (CFRP) composites: A review
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Publication Date
Fri Mar 01 2024
Journal Name
Baghdad Science Journal
Exploring the Challenges of Diagnosing Thyroid Disease with Imbalanced Data and Machine Learning: A Systematic Literature Review
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Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

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Publication Date
Sat Nov 01 2025
Journal Name
Journal Of Engineering
Improvement of Hot Mix Asphalt Resistance to Permanent Deformation at High Temperature Using Nanomaterial Modifiers: A Review
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The integration of nanomaterials in asphalt modification has emerged as a promising approach to enhance the performance of asphalt pavements, particularly under high-temperature conditions. Nanomaterials, due to their unique properties such as high surface area, exceptional mechanical strength, and thermal stability, offer significant improvements in the rheological properties, durability, and resistance to deformation of asphalt binders. This research reviewed the application of various nanomaterials, including nano silica, nano alumina, nano titanium, nano zinc, and carbon nanotubes in asphalt modification. The incorporation of these nanomaterials into asphalt mixtures has shown potential to increase the stiffness and high-tempera

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Publication Date
Thu May 21 2026
Journal Name
Scientific Reports
Prediction of unerupted canines and premolars widths in an Emirati population: development and validation of regression and machine learning models
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Abstract<p> This study aimed to develop a more accurate model for predicting the widths of unerupted canines and premolars in Emirati children, using deep learning and machine learning techniques. Dental models of 380 Emirati individuals aged 15–30 years were collected. The mesiodistal widths of permanent teeth were measured with a standardized orthodontic digital caliper. Regression models were developed using linear regression, Support Vector Regression (SVR; machine learning), and Artificial Neural Networks (ANN; deep learning). The widths of mandibular lateral incisors, central incisors, and the summed width of mandibular incisors were used as predictors. A two-tail</p> ... Show More
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