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The early and accurate prediction of liver disease in patients is still a challenging task among medical practitioners even with latest advanced technologies. The support vector machines are widely used in medical domain. It has proved its efficiency on producing good diagnostic parameters. These results can be further improved by optimizing the hyperparameters of support vector machines. The proposed work is based on optimizing support vector machines with crow search algorithm. This optimized support vector machine classifier (CSA-SVM) is used for accurate diagnosis of Indian liver disease data. The various similar state of art algorithms are taken for comparison with proposed approach to prove its efficient. The performance of CSA-SVM is found to be outstanding among all other approaches in terms of all metrics taken for comparison. It has yielded the classification accuracy of 99.49%.

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Artificial intelligence (AI) aims at critically transforming the information and communication technology (ICT) sector through various technological advancements, such as machine learning, deep learning, and natural language processing. These technologies are meant to develop the process of communication, digital commerce, content, and apps. AI is also meant to initiate novel business frameworks and formulate a completely novel business opportunity as efficiencies and interfaces facilitate the engagement, which has been heretofore unintelligible. A number of industry verticals will be changed through this form of evolution, as digital and ICT technologies are critical in supporting the various aspects of industrial operations, which include sales, marketing processes, supply chains, product and service delivery, and support frameworks. For instance, substantial implication of the frameworks can be witnessed in medical and bioinformatics, including the financial service segments. Workforce automation is a field that will influence various industrial verticals, as AI significantly develops the flow of work, accelerations, and processes of the return on investment for intelligent workplace application. This paper signifies the role of AI in ICT education, including the way intelligent ICT education has significantly developed its application and challenges. K E Y W O R D S artificial intelligence (AI), deep learning (DL), information and communication technology (ICT), machine learning (ML)