## 3 Classification Framework for Analysis
### Advantages and Drawbacks for the Healthcare Sector  
Contrasting positive and negative aspects of the healthcare industry, AI provides a number of advantages to people, some of which include streamlined decision making [10; 11; 12; 19; 61], health surveillance, including monitoring of elderly patients [13; 53; 69; 72; 85], early diagnosis [11; 50; 51; 70; 86; 87] and process simplification [19; 37; 62]. The acquired medical data of individuals, which are frequently inconsistent, convoluted, and not standardized, are the primary source of the barriers that accrue to those persons. In addition to that, they frequently come in a high volume and have a variety of forms to choose from. AI may be considered extremely successful in assessing such kinds of big data while producing creative suggestions that are highly pertinent and important for medical practitioners, which will ultimately benefit patients in their care, diagnosis, and therapeutic options. Despite the fact that this presents an enormous obstacle for health practitioners, AI can be very operational in analyzing these types of big data. Decisions pertaining to diagnosis and therapy typically require a lot of both time and effort. AI is a practical answer to this problem since it has the potential to generate autonomous inferences with little or no involvement from a human being. This makes it an ideal tool for overcoming this obstacle. According to [PERSON] et al. [24], some studies claim that AI can even surpass humans in certain medical settings, such as those involving radiology, cardiology, and tumor identification. [PERSON] and [PERSON] [19] discuss the case of chronic diseases. They state that chronic diseases in particular are taxing on the medical industry regarding effort and cost. This is due to the fact that patients with chronic diseases need constant treatment, which requires them to contact their healthcare providers on a regular basis. There are some of these visits that are completely pointless, which results in a waste of time and resources. According to the authors, they conclude with a strategy that combines health coaching with AI in order to assist patients in more efficiently managing their chronic diseases and reduce the number of visits that are not essential. This system, which is very similar to the one proposed by [PERSON] et al. [84], is made up of sensors that are able to collect biometric data, AI models that are able to create insights about health issues, and visual analytics tools that are able to display relevant data in graphical and textual formats. AI applications and IT tools are used by organizations in order to cut costs [19; 20; 24; 88], detect fraud [17; 89], improve performance [10; 27; 51], and provide workflow assistance [37; 39; 14]. For example, [PERSON] et al. [84] highlight the challenge of automatically extracting knowledge using medical IS. This difficulty is mostly due to the limited level of data standardization and integration that is present in these systems. In order to conquer these obstacles, the authors propose a synthetic network powered by AI. This is done on top of the original notes made by doctors in order to assure data normalization and integration from many sources. The operation of this network is comprised of three primary steps. First, it applies the transformation rules that have been stated to normalize the data. The data are then integrated after being transformed using ontologies that have been verified. In the end, it utilizes a model for data analytics in order to get useful information from the combined data. AI has been proposed as a solution for similar complications in the healthcare sector to reduce the consumption of resources [19; 20; 24; 88]. Many studies have implemented AI as a solution for analogous challenges. The detection of fraudulent claims is another area in which AI can be of use to the healthcare industry. The insurance industry has a significant obstacle in the form of fraudulent activity involving health insurance.