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Deep Learning Techniques in the Cancer-Related Medical Domain: A Transfer Deep Learning Ensemble Model for Lung Cancer Prediction
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Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a CT lung cancer dataset consisting of 1000 images and four different classes. The data augmentation process is applied to prevent overfitting, increase the size of the data, and enhance the training process. Score-level fusion and ensemble learning are also used to get the best performance and solve the low accuracy problem. All models were evaluated using accuracy, precision, recall, and the F1-score. Results: Experiments show the high performance of the ensemble model with 99.44% accuracy, which is better than all of the current state-of-the art methodologies. Conclusion: The current study's findings demonstrate the high accuracy and robustness of the proposed ensemble transfer deep learning using various transfer learning models

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Publication Date
Tue Dec 01 2015
Journal Name
International Journal Of Current Microbiology And Applied Sciences
Expression Analysis of Salivary Microrna-31 in Oral Cancer Patients
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Oral carcinoma is the 6th most common cancer in the world. MicroRNAs are small non-coding single stranded RNAs. They have been shown to be capable of altering mRNA expression; thus some are oncogenic or tumor suppressive in nature. The salivary microRNA-31 has been proposed as a sensitive marker for oral malignancy since it was abundant in saliva more than in plasma. A total of 55 whole saliva samples were collected from 35 cases diagnosed with OC their ages and gender matched with 20 healthy subjects. TaqManq RT-PCR was performed for RNA samples. Mean age was 52.23+13.73 years in cases (range:17-70 years) with male predominance represented 69%. Risk of smoking and alcoholism was highly significant. The median fold change of miR-31 was sign

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Publication Date
Sun Aug 28 2016
Journal Name
World Journal Of Pharmacy And Pharmaceutical Sciences
AN INSIGHT ON THE IDENTIFICATION OF CANCER STEM CELLS USING NOVEL IMMUNOLOGICAL AND MOLECULAR STRATEGIES
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Cancer stem cells (CSCs) are defined as a population of cells present in tumours, which can undergo self-renewal and differentiation. Identification and isolation of these CSCs using putative surface markers have been a priority of research in cancer. With this background we selected pancreatic normal and tumor cells for this study and passaged them into animal tissue culture medium. Further staining was done using alkaline phosphatase and heamatoxilin staining. Blue to purple colored zones in undifferentiated pluripotent stem cells and clear coloration in the chromatin material indicated pancreatic cells. Further studies on the cell surface marker CD 44 were done using ELISA. For this, the protein was extracted from cultivated normal and t

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Publication Date
Thu Oct 29 2020
Journal Name
Complexity
Training and Testing Data Division Influence on Hybrid Machine Learning Model Process: Application of River Flow Forecasting
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The hydrological process has a dynamic nature characterised by randomness and complex phenomena. The application of machine learning (ML) models in forecasting river flow has grown rapidly. This is owing to their capacity to simulate the complex phenomena associated with hydrological and environmental processes. Four different ML models were developed for river flow forecasting located in semiarid region, Iraq. The effectiveness of data division influence on the ML models process was investigated. Three data division modeling scenarios were inspected including 70%–30%, 80%–20, and 90%–10%. Several statistical indicators are computed to verify the performance of the models. The results revealed the potential of the hybridized s

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Publication Date
Mon Sep 29 2025
Journal Name
Journal Of Physical Education
The impact of proposed approach for flexibility and agility in learning some basic skills on the table land movements in the artistic gymnastics
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Publication Date
Wed Mar 15 2023
Journal Name
Bionatura
Cytotoxic potential activity of quercetin derivatives on MCF-7 breast cancer cell line
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Many previous investigations have found quercetin to be a powerful antioxidant and antitumor flavonoid, but its poor bioavailability has limited its use. This current study investigated the effects of two newly synthesized Quercetin Schiff bases containing 2-amino thiadiazole-5-thiol (Q1), and its benzyl derivatives (Q2) on MCF-7 human breast cancer cells. Cell viability and apoptosis were assessed to determine the toxic effects of Q1 and Q2. Cytotoxicity valuation showed that both compounds inhibited MCF-7 cell growth, and lactate dehydrogenase (LDH) activity increased in a dose-dependent aspect compared to the control group. Comet assay results observed that Q1 and Q2 induce more serious DNA damage than the control (untreated cell

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Publication Date
Mon Apr 01 2019
Journal Name
Iraqi Journal Of Biotechnology
The Promising Anti-Tumor Impact of Newcastle Disease Virus Expressing IL-2 and P53 Genes in Many Cancer Cell Lines In vitro
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Abstract: Recombinant Newcastle disease virus (rNDV) has shown an anticancer effect in preclinical studies, but has never been tested in a lung cancer models. In this study we explored the anticancer activity of genetically modified NDV expressing IL-2-P53 (rClone30–IL-2-P53) in lung cancer model. We have cloned IL-2 and P53 genes and inserted them in the viral genome of New Castle Disease Virus to create a genetically modified rNDV- IL-2-P53 virus and tested the anti-tumor activity of the new virus in vitro on different types of cancer cell lines by MTT assay. TheIL-2 and P53 gene were successfully cloned and inserted into the viral genome by using a Mlu I and Sfi I endonucleases, viral vector was constructed correctly and successf

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Publication Date
Mon Jun 01 2020
Journal Name
P J M H S
The influence of Breast Cancer Molecular Subtypes on Metastatic pattern in Iraqi patients
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Publication Date
Thu Mar 30 2017
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
The In Situ Expression of IL-6 and IL-1? in breast cancer patients
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Breast cancer is the second most common cancer in women world. Multiple Cytokines appear to have a dominant role in human breast cancer formation. Estimation of the in situ expression of  IL-6 and IL-1β in breast cancer patients. A sixty patients with breast cancer BC were divided into two clinical subgroups, (30) with malignant breast cancer MBC and (30) with benign breast tumor as a control group according to histological examination. In situ hybridization technique used for detection of IL-6 and IL-1β mRNA sequence in two groups.  The results showed that percentages of mRNA expression of IL-6 and IL-1β were in (≥ 11-50%) for malignant breast cancer. This research also investigated that (73.3%) of beni

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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Synthesis, Characterization of Poly Heterocyclic Compounds, and Effect on Cancer Cell (Hep-2) In vitro.
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A synthesis series of new heterocyclic derivatives (A2-A7) (pyrrole, pyridazine, oxazine and imidazol) derived from 4-acetyl-2,5-dichloro-1-(3,5-dinitrophenyl)-1H-pyrrole-3-carboxylate(A1) have been synthesised. Synthesis of compound (A2) by the reaction of starting material (A1) with hydroxyl amine hydrochloride in the presence of pyridine. Compound (A2) was reacted with hydrazine hydrate in dry benzene to give (A3) derivative. The compound )A3( deals with sodium nitrite to give diazonium salt, and the reaction diazonium salt with ethyl acetoacetate to produce compound (A4). To a mixture of compound (A4) and hydroxyl amine with sttired to yield (A5).Compound (A6) was prepared by reaction compound (A4) with thiosemicarbazide in presence

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Publication Date
Wed Sep 01 2010
Journal Name
Al-khwarizmi Engineering Journal
Prediction of the Scale Removal Rate in Heat Exchanger Piping System Using the Analogies between Mass and Momentum Transfer
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The possibility of predicting the mass transfer controlled CaCO3 scale removal   rate has been investigated.

Experiments were carried out using chelating agents as a cleaning solution at different time and Reynolds’s number. The results of CaCO3 scale removal or (mass transfer rate) (as it is the controlling process) are compared with proposed model of prandtl’s and Taylor particularly based on the concept of analogy among momentum and mass transfer.

Correlation for the variation of Sherwood number ( or mass transfer rate ) with Reynolds’s number have been obtained .

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