Challenges facing AI and Big data for Resource-poor Healthcare System

Abstract

During the last decade, major advancements in the health-care system have developed by offering numerous benefits to the patients throughout the world but resource-poor countries are not benefited through the best practices of health-care due to the lack of educated health-care providers, infrastructure, financial and technical issues, etc. Health-care systems in resource-poor countries face many challenges including increased healthcare cost, patient safety, overtreatment and failure to adopt best practices for health-care. In such countries, massive data generate from various resources including medical imaging, patient record, pharmaceutical reports, and medical devices. The exponential growth in medical data and advancement in health-care technologies focus data analysts to come up with innovative solutions for improving health-care practices in poor countries. Big data analytics provide tools to collect manage and analyze structured and unstructured medical data to find useful insights. Complexity and volume of medical data also show that, Artificial intelligence (AI) has the ability to approximate conclusions without direct human input, which can be applied in the health-care system of resource-poor countries and is now being utilized to further develop health services in high-income countries. Numerous investigations show that, AI performs better than humans in certain health-care undertakings such as diagnosis of cancer, tumor, heart diseases, radiology, etc. Popular AI techniques include machine learning methods such as neural network, support vector machine, and deep learning for structured data as well as natural language processing for unstructured data. There is a variety of hurdles around the use of big data and AI in health-care includes regulation, permission, transparency, and accountability. Also, the collection of data from an individual-a prerequisite for big data analytics is a technical and ethical issue. There are a lot of challenges for AI and big data in health-care but efforts need to be made before these techniques can be deployed in ethical and safe way. In this chapter, we discuss the challenges that AI and big data techniques face in resource-poor health care system and how it can be used to improve health outcomes in resource-poor countries.

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