Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

The rhetoric is concerned with the expressive emphasis of things, the science of the statement takes the treatment of graphic images and rhetorical fiction, and in the science of the exquisite dealing with the study of verbal and moral improvements, and in the science of meanings took all related to compositions and methods, and these vocabulary entered into the field of art and its branches largely, especially in the uncle and art of design because it has a major role in including a lot of biological functions with a deep meaning of its comprehensiveness on the multiplicity of real meanings characterized by suggestive and important and semantics refer to the recipient in the research to refer to the recipient The discovery of the intern

The term "semantic exchange" was popularized in Arabic, especially in derivatives, grammatical structures, etc., but it came under different names or terms, including deviation, deviation, transition, displacement, tooth breach, replacement, attention, etc. In the rooting of this term through its study in language and terminology, and among linguists, grammar and others, we have reached a number of results, including The existence of a harmonization between the lexical and idiomatic meaning of the term exchange, and the phenomenon of semantic exchange is a form of expansion in language, and that the first language scientists They had turned to this And studied under Cairo for different names, as noted above.

Recent studies have tended to look at Mottagorat texts for seeking more of the information provided by the book for the reader, has been known by several terms Mottagorat texts, including thresholds, including the margins of the text and the parallel texts, and came this difference, according to researchers who ate the subject of research and investigation. Thus, the researchers assert that all these texts must be subjected to provide information even if propaganda of the text. Hence arose the importance of these texts in Informatics scientific material being wrapped body of the text as well as being propaganda material to evoke the recipient to read, and then to the importance of this topic, the search came on five chapters, the first c

The COVID-19 pandemic has necessitated new methods for controlling the spread of the virus, and machine learning (ML) holds promise in this regard. Our study aims to explore the latest ML algorithms utilized for COVID-19 prediction, with a focus on their potential to optimize decision-making and resource allocation during peak periods of the pandemic. Our review stands out from others as it concentrates primarily on ML methods for disease prediction.To conduct this scoping review, we performed a Google Scholar literature search using "COVID-19," "prediction," and "machine learning" as keywords, with a custom range from 2020 to 2022. Of the 99 articles that were screened for eligibility, we selected 20 for the final review.Our system

Machine Learning (ML) algorithms are increasingly being utilized in the medical field to manage and diagnose diseases, leading to improved patient treatment and disease management. Several recent studies have found that Covid-19 patients have a higher incidence of blood clots, and understanding the pathological pathways that lead to blood clot formation (thrombogenesis) is critical. Current methods of reporting thrombogenesis-related fluid dynamic metrics for patient-specific anatomies are based on computational fluid dynamics (CFD) analysis, which can take weeks to months for a single patient. In this paper, we propose a ML-based method for rapid thrombogenesis prediction in the carotid artery of Covid-19 patients. Our proposed system aims

This paper proposes a better solution for EEG-based brain language signals classification, it is using machine learning and optimization algorithms. This project aims to replace the brain signal classification for language processing tasks by achieving the higher accuracy and speed process. Features extraction is performed using a modified Discrete Wavelet Transform (DWT) in this study which increases the capability of capturing signal characteristics appropriately by decomposing EEG signals into significant frequency components. A Gray Wolf Optimization (GWO) algorithm method is applied to improve the results and select the optimal features which achieves more accurate results by selecting impactful features with maximum relevance