The integration of AI technologies is revolutionizing various aspects of the apparel and textile industry, from design and manufacturing to customer experience and sustainability. Through the use of artificial intelligence algorithms, workers in the apparel and textile industry can take advantage of a wealth of opportunities for innovation, efficiency and creativity.
The research aims to display the enormous potential of artificial intelligence in the clothing and textile industry through published articles related to the title of the research using the Google Scholar search engine. The research contributes to the development of the cultural thought of researchers, designers, merchants and the consumer with the importance of integrating artificial intelligence technologies in the fields of the clothing and textile industry to keep pace with technological change.
The research found that the number of results for articles published in Google Scholar in the period of time from (2016-2023 AD) amounted to 1724, and 523 articles were published at a rate of (30%), which is the highest percentage for articles published in Google Scholar, and it was the lowest period of time from 2016-2017 AD. 50 published articles (3%), and the research recommended conducting more studies in the field of artificial intelligence and its applications in the clothing and textile industry.
Background: Plants used in folk medicine for
the treatment of peptic ulcer diseases is a very
promising approach to overcome the limitations of
classical medicines.
Aim: To explore the efficacy of medicinal
plants, namely turmeric, garlic and marshmallow,
in eradication of H. pylori.
Methods: This prospective study was carried out
on 225 of well-known dyspeptic patients who were
divided into four groups; a control group (received
classical medical therapy) and three other groups
that received one of the three medicinal plants,
plus the same therapy used in the control group.
The follow up was done by using a questionnaire
form, endoscopic examination, and determination
of serum levels of anti
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