Artificial Intelligence Issues in Healthcare

Abstract

Artificial Intelligence has been used in a variety of fields during the last many years, including search engines, machine-translation tools, intelligent personal assistants, electrical & electronics mechanism, media & entertainment, education, the automobile industry, and dynamically in healthcare. The growing use of machine learning, deep learning, robotics, natural language processing & other AI subsets is increasing every day. Electronic health records (EHRs), AI-enabled applications, medical data analysis, disease prediction, and many others are in use to upgrade healthcare services. AI-enabled applications/systems are used for the analysis of clinical trials, diagnosis, treatment, and prediction of future risks. There are many challenges/issues of AI implementation in healthcare due to its direct connection with human life. The elementary issues, such as privacy, security & integrity, need to focus on developing any AI-enabled medical services. The technical implementation issues such as data collection, relevance of data, flexible sample size, and discriminatory biases are very complex to address as the dynamic need. The emergence of new trends with specific analysis, diagnosis & prediction accurately is also a high challenge for AI-enabled healthcare services. One of the major concerns of ethical issues for AI implementation is the required huge effort.

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