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In this section, we present the effect of AI in healthcare for diagnosis application with examples. A simple process of AI transformation is shown in Figure 1.3. Online-based application has been developed to ease the process and increases real-time availability and accessibility of health-related information. Online healthcare has set a new channel for data transfer between the patient and the health unit. Extracting and analyzing the health record is a challenging task, which is achieved by reliable AI algorithms. These algorithms can predict the disease by understanding the nature of the patient’s record. Deep learning–based risk scoring and stratification tools are successfully developed to identify probable correlation from an unknown dataset within the patient’s record.

Application of AI in healthcare is utilized for acquiring a huge amount of data, processing the complex inheritance in them, and supporting decisions in case of the limited human intervention [10]. AI’s processing capabilities overcome the limitations mentioned above in healthcare and new methods to help doctors. AI is mainly used in diagnosing the illness compared with prognosis and therapy. Diagnosis is the process of observing and testing the patient, collecting information, analyzing the data, and finally providing a treatment plan. Diagnosis in AI is achieved by feeding patient information to the computing system, which produces diagnosis output.

Figure 1.3 AI-based diagnosis process.