The Role of Methods and Applications of Artificial Intelligence Tools in the Field of Medicine to Diagnose and Discover Various Diseases

Ahmed Hammad Al-Shoteri

Abstract


The use of AI in healthcare has increased. It is now used in diagnosis, drug production, and improving hospital workflow between medical departments. The ability to examine large numbers of patients quickly is also a major use of artificial intelligence. Indeed, this field has made remarkable advances in early diagnosis and discovery of diseases through data, information, and radiograph analysis. The ability to predict disease outbreaks using AI analytics is dependent on data analysis and disease prediction. The current study aimed to assess the validity of previous research on artificial intelligence applications and their role in diagnosing and discovering diseases. This is to fill several gaps, such as the lack of recent studies in this field, especially Arab studies. The study also seeks to understand how artificial intelligence tools can help diagnose and discover diseases. The study yielded several findings. It is necessary to design systems and algorithms, as well as mechanisms and methods, to fully utilize artificial intelligence in this field. Neural networks, deep learning, fuzzy logic and others were addressed in previous studies, for their adoption and possible application because of their great impact according to the results of previous studies. Artificial intelligence can simultaneously monitor and process an unlimited number of inputs, revealing complex correlations that cannot be easily reduced. Finally, the researcher believes that artificial intelligence will increase efficiency, save time and effort, and reduce errors. Also, AI does not replace doctors because it lacks human qualities like empathy and compassion. The use of artificial intelligence in medicine will thus contribute to an approved and unprecedented scientific approach in this field to achieve the desired goals and objectives.


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Keywords


Artificial Intelligence; Neural Networks; Deep Attachment; Fuzzy Logic

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