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Radiological Significance of Shear-Wave Elastography Technique for Evaluation of Solid Breast Masses with Histopathological Correlation
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Background: Although various imaging modalities are available for evaluating suspicious breast lesions, ultrasound-based Shear-Wave Elastography (SWE) is an advanced, non-invasive technique complementary to grayscale sonography. This technique evaluates the elasticity of a specific tissue by applying sonic pressure to that tissue.

Objective: The aim is to assess the role of SWE in evaluating solid breast masses in correlation to histopathological study results.

Subjects and Methods: This prospective study was done in a tertiary care teaching hospital from September 2019 to August 2020. A study population of 50 women aged 18 years or above with an ultrasonographic (USG) diagnosis of solid breast masses was included.

Results: A significantly higher value of SWE elasticity ratio (E-mean) was observed in malignant tumors than in benign tumors (p <0.0001).  The area-under-curve (AUC) for the BI-RADS 4 lesions was 0.522 (95% CI, 0.343-0.701) with an E-ratio cut-off score of 85.25, the sensitivity and specificity were 50% for diagnosing malignant tumors, whereas AUC for the HPE study was 1.000 (95% CI, 1.000-1.000) with an E-ratio cut-off score of 134.25; both the sensitivity and specificity were 100% for diagnosing malignant tumors.

Conclusions: Carcinoma breast is one of the most prevalent cancers globally. The most common benign tumor of the breast is a fibroadenoma, whereas Invasive Ductal Carcinoma is the most common malignant breast mass. A well-defined SWE elasticity ratio range might help predict the aggressiveness of breast tumors. SWE's correlation with BI-RADS in suspicious lesions adds to histopathology's advantage in distinguishing malignant tumors from benign ones.

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Publication Date
Wed Nov 02 2022
Journal Name
Turkish Journal Of Computer And Mathematics Education (turcomat)
Mpeg-Dash System via HTTP2 Protocol with HEVC Encoder for Video Streaming Services
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MPEG-DASH is an adaptive bitrate streaming technology that divides video content into small HTTP-objects file segments with different bitrates. With live UHD video streaming latency is the most important problem. In this paper, creating a low-delay streaming system using HTTP 2.0. Based on the network condition the proposed system adaptively determine the bitrate of segments. The video is coded using a layered H.265/HEVC compression standard, then is tested to investigate the relationship between video quality and bitrate for various HEVC parameters and video motion at each layer/resolution. The system architecture includes encoder/decoder configurations and how to embedded the adaptive video streaming. The encoder includes compression besi

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Publication Date
Fri Sep 01 2023
Journal Name
The Medical Journal Of Malaysia
Serum interleukin-40: an innovative diagnostic biomarker for patients with systemic lupus erythematosus
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Publication Date
Tue Oct 18 2022
Journal Name
Bulletin Of Materials Science
Highly crystalline anatase TiO2 nanotubes array films enhanced with Bi2S3 for photoelectrochemical applications
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Publication Date
Fri Mar 06 2026
Journal Name
International Journal Of Robotics And Control Systems
Integrating Multimodal Emotion Recognition with Deep Q-Learning for Adaptive Social Robot Interaction
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Publication Date
Sun Jan 01 2017
Journal Name
Iec2017 Proceedings Book
Improving TF-IDF with Singular Value Decomposition (SVD) for Feature Extraction on Twitter
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Publication Date
Wed Oct 01 2025
Journal Name
Journal Of Environmental Management
Induced electro-fenton process with a new electrochemical reactor design for tetracycline degradation
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Publication Date
Wed Oct 09 2024
Journal Name
Engineering, Technology &amp; Applied Science Research
Improving Pre-trained CNN-LSTM Models for Image Captioning with Hyper-Parameter Optimization
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The issue of image captioning, which comprises automatic text generation to understand an image’s visual information, has become feasible with the developments in object recognition and image classification. Deep learning has received much interest from the scientific community and can be very useful in real-world applications. The proposed image captioning approach involves the use of Convolution Neural Network (CNN) pre-trained models combined with Long Short Term Memory (LSTM) to generate image captions. The process includes two stages. The first stage entails training the CNN-LSTM models using baseline hyper-parameters and the second stage encompasses training CNN-LSTM models by optimizing and adjusting the hyper-parameters of

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Publication Date
Wed Feb 01 2017
Journal Name
Journal Of Controlled Release
Surface engineering tumor cells with adjuvant-loaded particles for use as cancer vaccines
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Publication Date
Fri Jun 30 2023
Journal Name
Iraqi National Journal Of Nursing Specialties
Instruction Program for Patient with Peptic Ulcer about Nutritional Habits: case-control study
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Objectives: The purpose of the study is to ascertain the relationship between the training program and the socio-demographic features of patients with peptic ulcers in order to assess the efficiency of the program on patients' nutritional habits.

Methodology: Between January 17 and October 30 of 2022, The Center of Gastrointestinal Medicine and Surgery at Al-Diwanyiah Teaching Hospital conducted "a quasi-experimental study". A non-probability sample of 30 patients for the case group and 30 patients for the control group was selected based on the study's criteria. The study instrument was divided into 4 sections: the first portion contained 7 questions about demographic information, the second sect

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Publication Date
Mon Dec 21 2020
Journal Name
2020 Emerging Technology In Computing, Communication And Electronics (etcce)
An Integrated Grey Wolf Optimizer with Nelder-Mead Method for Workflow Scheduling Problem
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