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A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for many applications dismissing the use of DL. Having sufficient data is the first step toward any successful and trustworthy DL application. This paper presents a holistic survey on state-of-the-art techniques to deal with training DL models to overcome three challenges including small, imbalanced datasets, and lack of generalization. This survey starts by listing the learning techniques. Next, the types of DL architectures are introduced. After that, state-of-the-art solutions to address the issue of lack of training data are listed, such as Transfer Learning (TL), Self-Supervised Learning (SSL), Generative Adversarial Networks (GANs), Model Architecture (MA), Physics-Informed Neural Network (PINN), and Deep Synthetic Minority Oversampling Technique (DeepSMOTE). Then, these solutions were followed by some related tips about data acquisition needed prior to training purposes, as well as recommendations for ensuring the trustworthiness of the training dataset. The survey ends with a list of applications that suffer from data scarcity, several alternatives are proposed in order to generate more data in each application including Electromagnetic Imaging (EMI), Civil Structural Health Monitoring, Medical imaging, Meteorology, Wireless Communications, Fluid Mechanics, Microelectromechanical system, and Cybersecurity. To the best of the authors’ knowledge, this is the first review that offers a comprehensive overview on strategies to tackle data scarcity in DL.</p>
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Publication Date
Sun Jan 01 2017
Journal Name
Iraqi Journal Of Medical Sciences
ISOLATION, IDENTIFICATION AND DETERMINATION OF ANTIFUNGAL SENSITIVITY OF FUNGI ISOLATED FROM A SAMPLE OF PATIENTS WITH RHINOSINUSITIS IN BAGHDAD CITY
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Publication Date
Mon Jan 01 2024
Journal Name
Oncology And Radiotherapy
Comparting study of cytokeratin 18 fragment M65 with CA19-9 and CEA as a biomarker in Iraqi colon cancer patients
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Publication Date
Tue Dec 14 2010
Journal Name
Applied Microbiology And Biotechnology
Elicitation of Streptomyces coelicolor with dead cells of Bacillus subtilis and Staphylococcus aureus in a bioreactor increases production of undecylprodigiosin
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Publication Date
Thu May 02 2013
Journal Name
Al-mustansiriyah
Synthesis, Spectroscopic and Biological Studies of a New some Complexes with N-Pyridine-2-Y1 methyl-benzene-1, 2-diamine.
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Publication Date
Wed Aug 31 2022
Journal Name
F1000research
Inflammatory markers in patients who presented with acute coronary syndrome and history of COVID-19 infection: a cross-sectional study
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Background: During the COVID-19 outbreak, the number of patients who have developed acute coronary syndromes (ACS) has soared rapidly, cardiovascular disease and mortality are influenced by the elevated inflammatory biomarkers. The aim of this study is to compare inflammatory markers between patients with ACS who hadn’t previously had COVID-19 and those who’d be infected within the preceding three months; as well as, evaluating the effect of statins on inflammatory biomarkers.

Methods: This is a comparative cross-sectional study of 42 patients who presented with ACS and had previously had COVID-19 and 48 patient who had never had CO

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Publication Date
Tue Oct 22 2019
Journal Name
Scientia Pharmaceutica
Design, Synthesis, and Docking Study of Acyl Thiourea Derivatives as Possible Histone Deacetylase Inhibitors with a Novel Zinc Binding Group
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Histone deacetylase inhibitors with zinc binding groups often exhibit drawbacks like non-selectivity or toxic effects. Thus, there are continuous efforts to modify the currently available inhibitors or to discover new derivatives to overcome these problems. One approach is to synthesize new compounds with novel zinc binding groups. The present study describes the utilization of acyl thiourea functionality, known to possess the ability to complex with metals, to be a novel zinc binding group incorporated into the designed histone deacetylase inhibitors. N-adipoyl monoanilide thiourea (4) and N-pimeloyl monoanilide thiourea (5) have been synthesized and characterized successfully. They showed inhibition of growth of human colon adenoc

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Publication Date
Sun Jan 01 2023
Journal Name
The Egyptian Journal Of Hospital Medicine
Association of Interleukin-12B Polymorphism and Serum Level of Interleukin-12 in a Sample of Iraqi Patients with Rheumatoid Arthritis
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Background In rheumatoid arthritis, your immune system attacks the tissue lining the joints on both sides of your body. Other parts of the body may also be affected. Unsure of the exact cause. Two separate genes termed IL12A (p35) and IL12 encode the heterodimeric cytokine known as IL12 (p40). Several different hematopoietic cell types can have several different hematopoietic cell types that can generate antigen-presenting cells (APCs), including DCs and macrophages. Objectives This study aimed to investigate if the interleukin IL-12B gene's common polymorphisms in an Iraqi population were associated with RA. Material and methods Blood samples were taken from 70 Iraqi patients with RA illnesses and 30 Iraqi controls during the periods from

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Publication Date
Sat Oct 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Strategic planning of human resources and its impact on the stages of a career path :A field research in the Ministry of Health
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Abstract

The objective of this research is to analyze the relationship between the strategic planning for human resources and career path, and I have tested Search the Ministry of  Health and some health centers headquarters in the Karkh district, that is applied in sample Consist of (45) Deputy Director, Head of Depts, Departmental Manager, and health center Manager.

Find interested in studying the two subjects are important and vital, at the level of organizations at the present time, namely the strategic planning of human resources and career path. To achieve the objectives of the research was designed Qusestionnair (31) items to collect  Primary data. and collected t

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Publication Date
Sat Oct 28 2023
Journal Name
Baghdad Science Journal
A Comparative Study on Association Rule Mining Algorithms on the Hospital Infection Control Dataset
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Administrative procedures in various organizations produce numerous crucial records and data. These
records and data are also used in other processes like customer relationship management and accounting
operations.It is incredibly challenging to use and extract valuable and meaningful information from these data
and records because they are frequently enormous and continuously growing in size and complexity.Data
mining is the act of sorting through large data sets to find patterns and relationships that might aid in the data
analysis process of resolving business issues. Using data mining techniques, enterprises can forecast future
trends and make better business decisions.The Apriori algorithm has bee

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Publication Date
Sun Mar 17 2019
Journal Name
Baghdad Science Journal
A Study on the Accuracy of Prediction in Recommendation System Based on Similarity Measures
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Recommender Systems are tools to understand the huge amount of data available in the internet world. Collaborative filtering (CF) is one of the most knowledge discovery methods used positively in recommendation system. Memory collaborative filtering emphasizes on using facts about present users to predict new things for the target user. Similarity measures are the core operations in collaborative filtering and the prediction accuracy is mostly dependent on similarity calculations. In this study, a combination of weighted parameters and traditional similarity measures are conducted to calculate relationship among users over Movie Lens data set rating matrix. The advantages and disadvantages of each measure are spotted. From the study, a n

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