Statistical learning theory serves as the foundational bedrock of Machine learning (ML), which in turn represents the backbone of artificial intelligence, ushering in innovative solutions for real-world challenges. Its origins can be linked to the point where statistics and the field of computing meet, evolving into a distinct scientific discipline. Machine learning can be distinguished by its fundamental branches, encompassing supervised learning, unsupervised learning, semi-supervised learning, and reinforcement learning. Within this tapestry, supervised learning takes center stage, divided in two fundamental forms: classification and regression. Regression is tailored for continuous outcomes, while classification specializes in categorical outcomes, with the overarching goal of supervised learning being to enhance models capable of predicting class labels based on input features. This review endeavors to furnish a concise, yet insightful reference manual on machine learning, intertwined with the tapestry of statistical learning theory (SLT), elucidating their symbiotic relationship. It demystifies the foundational concepts of classification, shedding light on the overarching principles that govern it. This panoramic view aims to offer a holistic perspective on classification, serving as a valuable resource for researchers, practitioners, and enthusiasts entering the domains of machine learning, artificial intelligence and statistics, by introducing concepts, methods and differences that lead to enhancing their understanding of classification methods.
Investigating the strength and the relationship between the Self-organized learning strategies and self-competence among talented students was the aim of this study. To do this, the researcher employed the correlation descriptive approach, whereby a sample of (120) male and female student were selected from various Iraqi cities for the academic year 2015-2016. the researcher setup two scales based on the previous studies: one to measure the Self-organized learning strategies which consist of (47) item and the other to measure the self-competence that composed of (50) item. Both of these scales were applied on the targeted sample to collect the required data
The emergence of COVID-19 has resulted in an unprecedented escalation in different aspects of human activities, including medical education. Students and educators across academic institutions have confronted various challenges in following the guidelines of protection against the disease on one hand and accomplishing learning curricula on the other hand. In this short view, we presented our experience in implementing e-learning to the undergraduate nursing students during the present COVID-19 pandemic emphasizing the learning content, barriers, and feedback of students and educators. We hope that this view will trigger the preparedness of nursing faculties in Iraq to deal with this new modality of learning and improve it should t
... Show MoreVolleyball is one of the sports that require physical and skill abilities thus many teaching models appeared to teach these abilities like group investigation model. The research aimed at identifying the effect of group investigation model on learning underarm and overhead passing in volleyball. The researchers hypothesized statistical differences between pre and posttests in learning underarm and overhead passing in volleyball as well as differences in posttests of controlling and experimental groups in learning underarm and overhead passing in volleyball. The researcher used the experimental method on (30) second year female students of physical education and sport sciences college/ university of Baghdad. Group investigation model was app
... Show MoreThe study aims at identifying the sources of information and explaining their role in e-learning from the viewpoint of the Iraqi college students. The researchers relied on the descriptive method of the survey method to collect data and know the point of view of undergraduate students from the Department of Information in the College of Arts / Tikrit University and the Department of Quranic Studies at the College of Arts / University of Baghdad. The questionnaire was used as an instrument of the study, the research sample is (120) students; each section has (60) male and female students. The study concluded that there are many types and forms of information sources that students receive through electronic educational platforms from text con
... Show MoreDiagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad
... Show MoreThe emergence of SARS-CoV-2, the virus responsible for the COVID-19 pandemic, has resulted in a global health crisis leading to widespread illness, death, and daily life disruptions. Having a vaccine for COVID-19 is crucial to controlling the spread of the virus which will help to end the pandemic and restore normalcy to society. Messenger RNA (mRNA) molecules vaccine has led the way as the swift vaccine candidate for COVID-19, but it faces key probable restrictions including spontaneous deterioration. To address mRNA degradation issues, Stanford University academics and the Eterna community sponsored a Kaggle competition.This study aims to build a deep learning (DL) model which will predict deterioration rates at each base of the mRNA
... Show MoreNeuro-ophthalmology, bridging neurology and ophthalmology, highlights the nervous system’s crucial role in vision, encompassing afferent and efferent pathways. The evolution of this field has emphasized the importance of neuroanatomy for precise surgical interventions, presenting educational challenges in blending complex anatomical knowledge with surgical skills. This review examines the interplay between neuroanatomy and surgical practices in neuro-ophthalmology, aiming to identify educational gaps and suggest improvements.
A literature search across databases such as PubMed, Scopus, and W
Dandruff and seborrheic dermatitis (SD) are common skin disorders affecting the scalp and extending to other body sites in the case of SD. They are associated with pruritus and scaling, causing an esthetical disturbance in the population affected. Treatment of such conditions involves using a variety of drugs for long terms, thus optimizing drug formulation is essential to improve therapeutic efficacy and patient compliance. Conventional topical formulations like shampoos and creams have been widely used but their use is associated with disadvantages. To overcome such effects, novel topical nanotechnology-based formulations are currently under investigation. In the following article, we highlight recently published formulatio
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