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Lung cancer classification using data mining and supervised learning algorithms on multi-dimensional data set
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These With recent developments in machine learning, data mining and computer vision, there is great potential for improvements in early detection of lung cancer using scans and data available. This paper details the methods and techniques used in our project, where the objective is to develop algorithms to determine whether a patient has or is likely to develop lung cancer using dataset images using data mining and machine learning for the classification and examination. We explore approaches to address the problem. Cancer is the most important cause of death globally. The disease diagnosis is a major process to treat the patients who are affected by cancer disease. The diagnosis process is more difficult comparatively known about the cancer disease detection. Developing a proposed data mining model is useful to diagnose the cancer disease once the cancer detection is accomplished using data mining for the examination and classification of machine learning supervised algorithms.

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Publication Date
Sat May 17 2014
Journal Name
Immunologic Research
Applying biodegradable particles to enhance cancer vaccine efficacy
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Publication Date
Fri Apr 12 2024
Journal Name
Revista Latinoamericana De Hipertension
Most common risk factors distribution for cervical cancer
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Publication Date
Mon Mar 06 2023
Journal Name
Biofactors
Mechanisms of cancer cell death induction by triptolide
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Abstract<p>Drug resistance is a hot topic issue in cancer research and therapy. Although cancer therapy including radiotherapy and anti‐cancer drugs can kill malignant cells within the tumor, cancer cells can develop a wide range of mechanisms to resist the toxic effects of anti‐cancer agents. Cancer cells may provide some mechanisms to resist oxidative stress and escape from apoptosis and attack by the immune system. Furthermore, cancer cells may resist senescence, pyroptosis, ferroptosis, necroptosis, and autophagic cell death by modulating several critical genes. The development of these mechanisms leads to resistance to anti‐cancer drugs and also radiotherapy. Resistance to therapy can increase mortal</p> ... Show More
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Publication Date
Thu Jul 27 2023
Journal Name
International Journal Of Medical Science In Clinical Research &amp; Review
Quality of life in female with breast cancer
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Background: The immediate effect of breast cancer and its treatment on the patient's psychological status and later adaptation of the patient with diagnosis and treatment of the disease may be led to disturbances in the quality of life of the patients. Objective: To measure Quality of life (QOL) in females with breast cancer, to find the factors that can improve their QOL and to identify the sociodemographic and clinical factors that have an influence on the QOL. Methods: The study sample was a convenient non-random sample of 103 patients diagnosed to have breast cancer at least one month after diagnosis. The data were collected by face-to-face interviews which took about 15-20 minutes with each patient, to fill out a standard questionnaire

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Publication Date
Thu Aug 31 2023
Journal Name
Oncology And Radiotherapy
The role of breath holding technique on minimizing cardiac dose in left breast cancer irradiation in the adjuvant setting
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Publication Date
Sun Jun 03 2012
Journal Name
Baghdad Science Journal
Evaluating the Inhibitory Activity of Apigenin Extracted from Salvia officinalis leaves on the Growth of L20B Cancer Cell Line
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The study aimed to evaluating the inhibitory activity of apigenin extracted from Salvia officinalis leaves on the growth of L20B cancer cell in vitro, and through two incubation periods; 48 and 72 hours. Accordingly, eight concentrations (1.56, 3.13, 6.25, 12.5, 25.0, 50.0, 100.0 and 200.0 micromol) of apigenin and similar concentrations of vitamin C and carbon tetrachloride (CCl4) were tested. The apigenin revealed its significant inhibitory potentials against the growth of L20B cell line, especially at the low concentrations (1.56, 3.13 and 6.25 micromol) and at 72 incubation period in comparison with vitamin C and CCl4.

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Publication Date
Sun Oct 09 2022
Journal Name
المجلة الع ا رقية لعلوم التربة
ISOLATION AND IDENTIFICATION OF MULTI-DRUD RESISTANCE STAPHYLOCOCCUS AUREUS WHICH ISOLATES FROM IRRIGATION AND WASTEWATER IN BAGHDAD CITY*
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A total number of 68 water samples was revealed 20 isolates being Staphylococcus aureus. Irrigation water isolates represented 25% of isolates while wastewater 75%. all isolates were identified by morphological, microscopial, biochemical tests and VITEK®2 Compact. Bacterial isolates were subjected to 16 antibiotics, all irrigation water and wastewater isolates were resistant to penicillin while they were fully sensitive to Ciprofloxcin. Irrigation water isolates showed relatively greater multi-drug resistance than wastewater, wherein irrigation water isolates showed 100% multi-drug resistance while wastewater isolates showed 73.3% multi-drug resistance, indicating the ability of S. aureus MDR to move from one site to another, which means t

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Publication Date
Thu Jun 01 2023
Journal Name
Iraqi Journal Of Physics
Design and Analysis of the Hexagonal-Shaped Antenna with Multi-Band Feature for WLAN, WiMAX, and LTE Applications
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Developing and researching antenna designs are analogous to excavating in an undiscovered mine. This paper proposes a multi-band antenna with a new hexagonal ring shape, theoretically designed, developed, and analyzed using a CST before being manufactured. The antenna has undergone six changes to provide the best performance. The results of the surface current distribution and the electric field distribution on the surface of the hexagonal patch were theoretically analyzed and studied. The sequential approach taken to determine the most effective design is logical, and prevents deviation from the work direction. After comparing the six theoretical results, the fifth model proved to be the best for making a prototype. Measured results rep

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Publication Date
Tue Apr 02 2019
Journal Name
Artificial Intelligence Research
A three-stage learning algorithm for deep multilayer perceptron with effective weight initialisation based on sparse auto-encoder
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A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an

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Publication Date
Sun Oct 18 2026
Journal Name
Journal Of Physical Education
The effect of the Perkins-Blyth model on learning some compound skills in soccer for second intermediate students
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