Diabetes in the Arab World

Khan, Rabia; Siddiqui, Ammar Ahmed; Alshammary, Freah; Shaikh, Sameer; Amin, Junaid; Rathore, Hassaan Anwer

doi:10.1007/978-3-030-36811-1_41

Cited by 2 publications

(2 citation statements)

References 109 publications

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“…Contemplate, for example, cardiomegaly, an often-undiagnosed condition. Amin and Siddiqui [39] provide a detailed discussion of this disorder including a definition, etiology, epidemiology, pathophysiology, and evaluation. Briefly, they define this condition in terms of an increased cardiothoracic ratio: the transverse diameter of the cardiac silhouette is greater than or equal to 50% of the transverse diameter of the chest as observed on a posterior-anterior projection of a chest radiograph or a computed tomography.…”

Section: Remote Patient Monitoringmentioning

confidence: 99%

Deep Neural Networks and Applications in Medical Research

Abut,

Okut,

Zackula

et al. 2024

Artificial Intelligence

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Artificial Intelligence (AI) has played a significant role in improving decision-making within the healthcare system. AI includes machine learning, which encompasses a subset called artificial neural networks (ANNs). These networks mimic how biological neurons in the brain signal one another. In this chapter, we conduct a seminal review of ANNs and explain how prediction and classification tasks can be conducted in the field of medicine. Basic information is provided showing how neural networks solve the problem of determining disease subsets by analyzing huge amounts of structured and unstructured patient data. We also provide information on the application of conventional ANNs and deep convolutional neural networks (DCNNs) that are specific to medical image processing. For example, DCNNs can be used to detect the edges of an item within an image. The acquired knowledge can then be transferred so that similar edges can be identified on another image. This chapter is unique; it is specifically aimed at medical professionals who are interested in artificial intelligence. Because we will demonstrate the application in a straightforward manner, researchers from other technical fields will also benefit.

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Section: Remote Patient Monitoringmentioning

confidence: 99%

Deep Neural Networks and Applications in Medical Research

Abut,

Okut,

Zackula

et al. 2024

Artificial Intelligence

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“…It is estimated that around 1.31 billion individuals worldwide could be living with the disease by 2050, with an overall global health expenditure of $1054 billion by 2045 [2]. Te prevalence of diabetes has also been on the rise in the Arab World in conjunction with suboptimal nutritional habits (either due to the spread of a "Westernized diet" or the lack of appropriate nutrition), sedentary lifestyle, and subsequent overweight and obesity [3]. Te Middle Eastern and North African (MENA) region has one of the rapidly increasing diabetes rates worldwide, with the number of individuals with diabetes expected to rise by 96.2% by 2035 [4].…”

Section: Background: An Eternity Of Diabetesmentioning

confidence: 99%

Diabetes Mellitus across the Arabo-Islamic World: A Revolution

Fleifel,

El Alam

2023

International Journal of Endocrinology

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Background. Mankind continues to suffer from the ever-growing diabetes epidemic and the rapid rise of type 2 diabetes mellitus (T2DM). This metabolic disease has been studied since ancient civilizations. The Arabo-Islamic civilization excelled in establishing some of the most notable discoveries and teachings that remained the blueprint for years to come in the field of diabetology. Aim. This article aimed to review the ancient history of diabetes mellitus, with its main focus on the Arabo-Islamic civilization, and to report our subjective views and analysis of some of the past recommendations based on modern-day findings. Discussion. It is natural to have the teachings of medicine dynamically inspired by one civilization to another, as various fields continue to expand and evolve. This also applies to diabetology as the Arabo-Islamic world used the outlines of prior civilizations to revolutionize the understanding of the disease. Al-Razi and Ibn Sina are probably two of the most renowned polymaths in history, and their contributions to diabetology are well documented. Ibn Maymun’s postulation about the higher prevalence of diabetes in Egypt as compared to Andalusia is something to be carefully studied. It could be that diabetes mellitus’ underdiagnosis and late-stage detection are some of the major reasons for the disparity between the two mentioned regions. Modern-day Arabo-Islamic scholars continue to excel in revolutionizing diabetology. Conclusion. The Arabo-Islamic world houses an impressive bout of scholars who have contributed since the ancient times to diabetology. This scientific locomotion shows no signs of stopping, as it continues to shine during the present day, and likely in the future.

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Diabetes in the Arab World

Cited by 2 publications

References 109 publications

Deep Neural Networks and Applications in Medical Research

Deep Neural Networks and Applications in Medical Research

Diabetes Mellitus across the Arabo-Islamic World: A Revolution

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